The goal of the FAITH project (Federated Artificial Intelligence solution for moniToring mental Health status after cancer treatment) is to remotely identify and predict depressive symptoms in cancer survivors using a federated machine learning approach that prioritizes privacy. The target audience includes healthcare professionals, researchers, technology developers and cancer survivors. The FAITH project leverages the following key areas of digital health: wearable technology, cloud-based technology, and predictive Artificial Intelligence (AI). As cancer survival rates rise due to improved screening and treatment, many survivors face long-term physical and psychological challenges, such as depression, anxiety, and cognitive impairment. Depression is more common in cancer survivors than in the general population, if untreated, can significantly reduce quality of life and increase healthcare needs. Overlapping symptoms like fatigue and sleep disturbances make it harder to differentiate depression from cancer-related effects.
Home / Publications / Publication
Home / Publications / Publication
ARTIFICIAL INTELLIGENCE USED IN DEPRESSION DETECTION IN CANCER SURVIVORS
Publication type: Article Summary
Original title: A prospective observational study for a Federated Artificial Intelligence solution for moniToring mental Health status after cancer treatment (FAITH): study protocol
Article publication date: December 2022
Source: BMC Psychiatry
Authors: Raquel Lemos, Sofia Areias-Marques, Pedro Ferreira, Philip O’Brien, María Eugenia Beltrán-Jaunsarás, Gabriela Ribeiro, Miguel Martín, María del Monte-Millán, Sara López-Tarruella, Tatiana Massarrah, Fernando Luís-Ferreira, Giuseppe Frau, Stefanos Venios, Gary McManus & Albino J. Oliveira-Maia
What is the goal, target audience, and areas of digital health it addresses?
The goal of the FAITH project (Federated Artificial Intelligence solution for moniToring mental Health status after cancer treatment) is to remotely identify and predict depressive symptoms in cancer survivors using a federated machine learning approach that prioritizes privacy. The target audience includes healthcare professionals, researchers, technology developers and cancer survivors. The FAITH project leverages the following key areas of digital health: wearable technology, cloud-based technology, and predictive Artificial Intelligence (AI).
What is the context?
As cancer survival rates rise due to improved screening and treatment, many survivors face long-term physical and psychological challenges, such as depression, anxiety, and cognitive impairment. Depression is more common in cancer survivors than in the general population, if untreated, can significantly reduce quality of life and increase healthcare needs. Overlapping symptoms like fatigue and sleep disturbances make it harder to differentiate depression from cancer-related effects.
Federated machine learning is a decentralized method that trains AI models across multiple devices without sharing personal data. Each device processes its own data and sends only updates to a central server, ensuring privacy. The server combines these updates to improve the overall model, then sends the refined version back to each device. This continuous process makes the predictions more accurate through collective learning, and also allows each device’s AI model to remain personalized, adapting to the user’s specific data.
What are the current approaches?
Traditional approaches to identifying depression in cancer survivors typically focus on the early years post-diagnosis, when patients are still in regular follow-up care. Current methods primarily rely on self-rated questionnaires, occasional clinical assessments, and symptom-based interviews. While these self-reporting tools are quick, easy, and cost-effective, they tend to miss key somatic symptoms like fatigue, appetite changes, and sleep disturbances. Additionally, these tools alone cannot provide a clinical diagnosis, which requires structured or semi-structured interviews. The infrequent follow-ups and reliance on subjective data often result in undetected cases of depression, especially after cancer treatment ends.
What does the FAITH project consist of? How is the impact of this FAITH project assessed?
The FAITH project consists of a privacy-focused AI system designed to provide real-time insights into patients’ mental health through the analysis of 4 key depression markers: Activity, Sleep, Nutrition, and Voice, using this data to predict the risk of depression. The FAITH app integrates both passive data collection (automatic tracking of sleep and physical activity via smartbands and smartphones) and proactive data collection (self-reporting of nutrition habits through validated questionnaires and voice recordings).
The FAITH project leverages federated machine learning, enabling AI models to be trained directly on users’ devices using local data from four key markers to predict depression risk. Statistical analyses, such as neural network modeling, further improve the accuracy of these predictions while incorporating bias reduction strategies. The platform operates on the Amazon Web Services (AWS) cloud, providing scalable storage and robust cybersecurity. This decentralized approach safeguards sensitive information, while data pseudonymization (replacing personal identifiers with coded identifiers) and strict compliance with General Data Protection Regulation (GDPR) standards ensure a high level of privacy and adherence to European data protection laws.
The impact of the FAITH project is assessed through a longitudinal prospective study involving 300 breast or lung cancer survivors, recruited 1 to 5 years post-treatment. Participants are continuously monitored for sleep and physical activity. Each month, they self-report anxiety and depression using the Hospital Anxiety and Depression Scale (HADS), assess their quality of life with the EORTC questionnaires, and complete nutrition assessments. They also do monthly voice recordings, as speech patterns can offer insights into emotional well-being. Every 3 months, participants fill the applicable sleep and eating behavior questionnaires, and a clinician conducts a phone assessment for depressive symptoms using the Hamilton Depression Rating Scale (Ham-D).
What are the predictable results? What is the future of FAITH project?
In the FAITH project, the user-friendly design and streamlined flow encourage consistent participation without overwhelming users. This regular engagement ensures high-quality data, enabling the algorithms to make accurate real-time predictions and trigger immediate alerts for healthcare professionals when depression markers exceed defined thresholds. The expected results include earlier detection of depressive episodes and timely interventions that improve patients’ quality of life and ease the burden on healthcare systems.
The future of the FAITH project goes beyond cancer care, with the potential to apply this privacy-focused digital health tool to other chronic diseases and mental health conditions. Its long-term success relies on refining the AI model, completing clinical trials, and continuously improving usability and feasibility based on feedback. Future updates will help healthcare professionals better understand how the AI reaches its conclusions, leading to more informed decision-making and more personalized interventions.
Would you like to know all the details?
Autonomous Robotics System for Autism Therapy
Autism spectrum disorder is a neurodevelopmental condition with significant clinical, social and economic repercussions throughout life. According to the World Health Organization, it is estimated…
Virtual Reality Exergames as a Tool for Diagnosing Eye Diseases
Eye diseases represent a growing public health challenge in Portugal, significantly compromising the population’s quality of life. The increase in their prevalence is associated with…
Improving Efficiency in the Clinical Follow-up for Covid-19 Cases With a Digital Platform
COVID-19, caused by the SARS-CoV-2 virus, is a highly contagious disease with the potential to cause serious complications, requiring the isolation of infected individuals and…
The Rising Threat of Antibiotic-resistant Klebsiella in Portuguese Hospitals
Healthcare-associated infections pose a serious public health threat, as they are acquired during medical treatments or hospital stays, often leading to prolonged hospitalizations, high costs…
Deep Neural Networks And The Future Of Early Detection Of Alzheimer’s Disease
Alzheimer’s disease is the most common form of dementia, affecting more than 55 million people globally and accounting for around 70 percent of dementia cases….
Mobile Application to Improve Workflows in Nursing Homes
Portugal has one of the highest aging populations in the world, placing increasing pressure on elderly care services, especially in nursing homes. Healthcare professionals in…
The Challenges of Data Protection in Digital Health Platforms for the Elderly
Demographic ageing poses significant challenges to healthcare systems, intensifying the pressure on infrastructures and human resources. It is estimated that by 2050 the elderly population…
Facilitating Epilepsy Diagnosis With a Wireless and Wearable EEG System
Paroxysmal diseases are characterized by sudden, episodic conditions that cause temporary changes in the body. Among them, epilepsy stands out for causing synchronous and uncontrolled…
Automatic Segmentation of Blood Vessels in Carotid Ultrasound Images
Vascular diseases, such as carotid stenosis (narrowing of the carotid arteries, which connect the heart to the brain, caused by the accumulation of fatty atheroma…
Impact of Robotherapy-PARO on Elderly People With Dementia in Portugal
Aging is a gradual, multifactorial and continuous process characterized by the progressive loss of biological function and degeneration associated with the onset of age-related diseases….
New Era of Interoperability in Healthcare Systems
The growing use of electronic health records, digital diagnostic systems and remote monitoring technologies has led to a significant increase in the volume and complexity…
Improvement in Breast Tumor Localization With an Image Fusion Algorithm
Breast-conserving surgery aims to remove tumors while preserving as much healthy breast tissue as possible, ensuring optimal aesthetic outcomes that are critical for a patient’s…
Collaborative Robotics Improves Working Conditions
Workers face growing challenges in the industrial environment. Among the most critical are fatigue and inappropriate postures, often associated with repetitive tasks and working conditions…
The Role of Mobile Technologies in the Monitoring and Rehabilitation of Peripheral Arterial Disease
PAD is a prevalent chronic condition, affecting approximately 200 million individuals globally, characterized by obstruction of the peripheral arteries, especially in the lower extremities, due…
Incorporation of Digital Implants Into CT Images to Plan Orthopedic Surgery
Orthopedic surgery addresses conditions of the musculoskeletal system to alleviate pain, restore function, and enhance the patient’s quality of life. Its success relies on meticulous…
Digital Health at the Top of the National Poliempreende 2024 Results
Poliempreende is a consolidated national network for encouraging entrepreneurship in higher education in Portugal, with two decades of existence. Focused on promoting innovation, the competition…
Digital Solution Facilitates Interaction Between Users and Health Professionals
Many patients face difficulties scheduling medical appointments in hospital units, and, when successful, they often endure long waiting times to be attended. This situation is…
The Impact of Calm Computing Integration on the Clinical Process
In recent years, digital transformation in healthcare has played a crucial role, driven by the exponential increase in medical data. This ranges from administrative information…
ULS Almada-Seixal Revolutionizes With the Region’s First Surgical Robot
In recent years, ULSAS has been gradually implementing robotic systems, reinforcing its commitment to innovation and improving healthcare. Recently, the institution acquired a state-of-the-art robotic…
Online Intervention Aims to Prevent Anxiety in the General Population
Anxiety disorders are a global problem, affecting 300 million people worldwide and placing significant pressure on individuals and healthcare systems. In Europe alone, the economic…
Rehabilitation of Facial Paralysis Through Virtual Assistants
Facial paralysis, defined by the inability to move one or both sides of the face, has an incidence of 20 to 30 cases per 100,000…
Detection of Anxiety and Panic Attacks in Real Time
The growing number of people with anxiety disorders, along with increased awareness of mental health, drives the need for new technological tools that provide remote…
A Novel Approach for Robotic-assisted Tele-echography
Currently, robotic systems for ultrasound diagnostic procedures fall into two main categories: portable robots that require manual positioning and fully autonomous robotic systems that independently…
From Big Data to Big Decisions: How AI Stratifies Cancer Cases by Risk Factors
The CLARIFY Decision Support Platform (DSP) is a responsive web application designed to support decision-making in cancer care through real-time data integration and predictive analytics….
From “Free Text” to Structured Clinical Data: the Foundation for Clinical Decision Support Systems
Currently, the practice of recording clinical information in “free text” offers flexibility, but hinders automatic data extraction, limiting the application of analytical models. Most records…
Integration of SONHO v2 and SClínico Systems at ULS of Coimbra to Improve Healthcare Services
With more than half a million hospital medical consultations carried out in the first half of 2024, the ULS of Coimbra stands out as an…
Elderly Care Ecosystem: an Innovative Platform for Personalized and Efficient Services
The Elderly Care Ecosystem (ECE) is an integration of various digital health technologies, exploring the areas of telehealth and predictive analytics. The goal of this…
Innovative technology that subconsciously relieves anxiety through a scarf
The SCAARF technology aims to offer an alternative method to alleviate anxiety symptoms in a non-intrusive and subconscious way. This technology is an innovative idea…
Digital Health Interventions: Equity in Hypertension Care for Everyone
Nearly half of all adults in the United States have hypertension, one of the leading risk factors for cardiovascular disease, and only about a quarter…
Personalization and Technology in Diabetes Management
IPDM has significant potential to improve diabetes management and drive health system reforms to become high-performing, effective, equitable, accessible, and sustainable. Evidence and good practices…
Negotiations on the European Health Data Space Advance With the Participation of the SPMS
The European Health Data Space will be a common health data sharing system across the European Union. It foresees the use of data for purposes…
Secretary of State Margarida Tavares Emphasizes Digital Innovation in Health Promotion
Margarida Tavares spoke at the opening of the conference ” O Digital na promoção contínua da saúde e do bem-estar”, organized by the Associação para…
ARS Algarve Modernizes Radiology With AI and New Data Center
The radiology service of ARS Algarve has already performed nearly 29,000 exams using Artificial Intelligence (AI) technology. In recent years, there has been a significant…
European Health Data Space: Unified Access To Health Data In The EU
The COVID-19 pandemic highlighted the importance of digital services in health, but complex rules and increasing cyberattacks make it difficult to share data across Member…
European Commission Amends Digital Europe Programme With an Investment of €762.7 Million
The European Commission has amended the Digital Europe Programme work programmes 2023-2024, investing an additional €762.7 million in Europe’s digital transition and cybersecurity. The digital…
SPMS Integrates the TEF-Health Initiative
SPMS participates in the TEF-Health initiative as a partner in a consortium composed of 51 entities from 9 European Union countries. This action is co-financed…
FMUP Creates Inhealth Junior Academy for High School Students
The InHealth Junior Academy — Academia Júnior de Inovação em Saúde is an initiative of the Departamento de Medicina da Comunidade, Informação e Decisão em…
SPMS Represents Portugal as Vice-president of GDHP
The GDHP is an intergovernmental organization in the digital health sector that facilitates cooperation and collaboration between government representatives and the World Health Organization (WHO)….
Digital Transformation of Health at INCoDe.2030 in Tomar
The “National Digital Skills Initiative e.2030, Portugal” (INCoDe.2030) is an initiative that aims to improve the Portuguese population’s level of digital skills, placing Portugal at…
Braga Hospital Evaluates Memory With Interactive Game in Patients With Multiple Sclerosis
Multiple Sclerosis is known as a chronic disease of the central nervous system, with a wide variety of motor and sensory symptoms that can lead…
Neurosurgery Teleconsultation Wins Innovation Award
The aim of the BI Award for Innovation in Healthcare is to recognize innovative projects in the healthcare sector that improve the quality of life…
HealthData@PT: New SPMS Initiative for Health Data
Action HealthData@PT is launched in the context of the implementation of the European Health Data Space, and is an initiative approved by the European Commission…
Do you have an innovative idea in healthcare field?
Share it with us and see it come to life.
We will help bring your projects to life!
Home / Publications / Publication
ARTIFICIAL INTELLIGENCE USED IN DEPRESSION DETECTION IN CANCER SURVIVORS
Publication type: Article Summary
Original title: A prospective observational study for a Federated Artificial Intelligence solution for moniToring mental Health status after cancer treatment (FAITH): study protocol
Article publication date: December 2022
Source: BMC Psychiatry
Authors: Raquel Lemos, Sofia Areias-Marques, Pedro Ferreira, Philip O’Brien, María Eugenia Beltrán-Jaunsarás, Gabriela Ribeiro, Miguel Martín, María del Monte-Millán, Sara López-Tarruella, Tatiana Massarrah, Fernando Luís-Ferreira, Giuseppe Frau, Stefanos Venios, Gary McManus & Albino J. Oliveira-Maia
What is the goal, target audience, and areas of digital health it addresses?
The goal of the FAITH project (Federated Artificial Intelligence solution for moniToring mental Health status after cancer treatment) is to remotely identify and predict depressive symptoms in cancer survivors using a federated machine learning approach that prioritizes privacy. The target audience includes healthcare professionals, researchers, technology developers and cancer survivors. The FAITH project leverages the following key areas of digital health: wearable technology, cloud-based technology, and predictive Artificial Intelligence (AI).
What is the context?
As cancer survival rates rise due to improved screening and treatment, many survivors face long-term physical and psychological challenges, such as depression, anxiety, and cognitive impairment. Depression is more common in cancer survivors than in the general population, if untreated, can significantly reduce quality of life and increase healthcare needs. Overlapping symptoms like fatigue and sleep disturbances make it harder to differentiate depression from cancer-related effects.
Federated machine learning is a decentralized method that trains AI models across multiple devices without sharing personal data. Each device processes its own data and sends only updates to a central server, ensuring privacy. The server combines these updates to improve the overall model, then sends the refined version back to each device. This continuous process makes the predictions more accurate through collective learning, and also allows each device’s AI model to remain personalized, adapting to the user’s specific data.
What are the current approaches?
Traditional approaches to identifying depression in cancer survivors typically focus on the early years post-diagnosis, when patients are still in regular follow-up care. Current methods primarily rely on self-rated questionnaires, occasional clinical assessments, and symptom-based interviews. While these self-reporting tools are quick, easy, and cost-effective, they tend to miss key somatic symptoms like fatigue, appetite changes, and sleep disturbances. Additionally, these tools alone cannot provide a clinical diagnosis, which requires structured or semi-structured interviews. The infrequent follow-ups and reliance on subjective data often result in undetected cases of depression, especially after cancer treatment ends.
What does the FAITH project consist of? How is the impact of this FAITH project assessed?
The FAITH project consists of a privacy-focused AI system designed to provide real-time insights into patients’ mental health through the analysis of 4 key depression markers: Activity, Sleep, Nutrition, and Voice, using this data to predict the risk of depression. The FAITH app integrates both passive data collection (automatic tracking of sleep and physical activity via smartbands and smartphones) and proactive data collection (self-reporting of nutrition habits through validated questionnaires and voice recordings).
The FAITH project leverages federated machine learning, enabling AI models to be trained directly on users’ devices using local data from four key markers to predict depression risk. Statistical analyses, such as neural network modeling, further improve the accuracy of these predictions while incorporating bias reduction strategies. The platform operates on the Amazon Web Services (AWS) cloud, providing scalable storage and robust cybersecurity. This decentralized approach safeguards sensitive information, while data pseudonymization (replacing personal identifiers with coded identifiers) and strict compliance with General Data Protection Regulation (GDPR) standards ensure a high level of privacy and adherence to European data protection laws.
The impact of the FAITH project is assessed through a longitudinal prospective study involving 300 breast or lung cancer survivors, recruited 1 to 5 years post-treatment. Participants are continuously monitored for sleep and physical activity. Each month, they self-report anxiety and depression using the Hospital Anxiety and Depression Scale (HADS), assess their quality of life with the EORTC questionnaires, and complete nutrition assessments. They also do monthly voice recordings, as speech patterns can offer insights into emotional well-being. Every 3 months, participants fill the applicable sleep and eating behavior questionnaires, and a clinician conducts a phone assessment for depressive symptoms using the Hamilton Depression Rating Scale (Ham-D).
What are the predictable results? What is the future of FAITH project?
In the FAITH project, the user-friendly design and streamlined flow encourage consistent participation without overwhelming users. This regular engagement ensures high-quality data, enabling the algorithms to make accurate real-time predictions and trigger immediate alerts for healthcare professionals when depression markers exceed defined thresholds. The expected results include earlier detection of depressive episodes and timely interventions that improve patients’ quality of life and ease the burden on healthcare systems.
The future of the FAITH project goes beyond cancer care, with the potential to apply this privacy-focused digital health tool to other chronic diseases and mental health conditions. Its long-term success relies on refining the AI model, completing clinical trials, and continuously improving usability and feasibility based on feedback. Future updates will help healthcare professionals better understand how the AI reaches its conclusions, leading to more informed decision-making and more personalized interventions.
Would you like to know all the details?
Autonomous Robotics System for Autism Therapy
Autism spectrum disorder is a neurodevelopmental condition with significant clinical, social and economic repercussions throughout life. According to the World Health Organization, it is estimated to affect approximately 1 in 160 children worldwide. Its origin…
Virtual Reality Exergames as a Tool for Diagnosing Eye Diseases
Eye diseases represent a growing public health challenge in Portugal, significantly compromising the population’s quality of life. The increase in their prevalence is associated with various factors, such as demographic ageing, excessive use of digital…
Improving Efficiency in the Clinical Follow-up for Covid-19 Cases With a Digital Platform
COVID-19, caused by the SARS-CoV-2 virus, is a highly contagious disease with the potential to cause serious complications, requiring the isolation of infected individuals and appropriate clinical follow-up. While severe cases require hospitalization, patients with…
The Rising Threat of Antibiotic-resistant Klebsiella in Portuguese Hospitals
Healthcare-associated infections pose a serious public health threat, as they are acquired during medical treatments or hospital stays, often leading to prolonged hospitalizations, high costs for healthcare systems and high mortality rates. Portugal has one…
Deep Neural Networks And The Future Of Early Detection Of Alzheimer’s Disease
Alzheimer’s disease is the most common form of dementia, affecting more than 55 million people globally and accounting for around 70 percent of dementia cases. In Portugal, it is estimated that 200,000 people live with…
Mobile Application to Improve Workflows in Nursing Homes
Portugal has one of the highest aging populations in the world, placing increasing pressure on elderly care services, especially in nursing homes. Healthcare professionals in these facilities are often overwhelmed due to the increasing number…
The Challenges of Data Protection in Digital Health Platforms for the Elderly
Demographic ageing poses significant challenges to healthcare systems, intensifying the pressure on infrastructures and human resources. It is estimated that by 2050 the elderly population will exceed 2 billion people, making it imperative to implement…
Facilitating Epilepsy Diagnosis With a Wireless and Wearable EEG System
Paroxysmal diseases are characterized by sudden, episodic conditions that cause temporary changes in the body. Among them, epilepsy stands out for causing synchronous and uncontrolled neuronal discharges, resulting in recurrent and unprovoked seizures. These seizures…
Automatic Segmentation of Blood Vessels in Carotid Ultrasound Images
Vascular diseases, such as carotid stenosis (narrowing of the carotid arteries, which connect the heart to the brain, caused by the accumulation of fatty atheroma plaques), cerebrovascular accidents (CVA) (sudden interruption of blood flow to…
Impact of Robotherapy-PARO on Elderly People With Dementia in Portugal
Aging is a gradual, multifactorial and continuous process characterized by the progressive loss of biological function and degeneration associated with the onset of age-related diseases. In Portugal, the aging of the population is particularly noticeable,…
New Era of Interoperability in Healthcare Systems
The growing use of electronic health records, digital diagnostic systems and remote monitoring technologies has led to a significant increase in the volume and complexity of health data. This increase intensifies the need for continuous,…
Improvement in Breast Tumor Localization With an Image Fusion Algorithm
Breast-conserving surgery aims to remove tumors while preserving as much healthy breast tissue as possible, ensuring optimal aesthetic outcomes that are critical for a patient’s quality of life. To achieve this objective, precise location of…
Collaborative Robotics Improves Working Conditions
Workers face growing challenges in the industrial environment. Among the most critical are fatigue and inappropriate postures, often associated with repetitive tasks and working conditions that lack ergonomic suitability. These factors represent significant risks for…
The Role of Mobile Technologies in the Monitoring and Rehabilitation of Peripheral Arterial Disease
PAD is a prevalent chronic condition, affecting approximately 200 million individuals globally, characterized by obstruction of the peripheral arteries, especially in the lower extremities, due to the formation of atherosclerotic plaques, which compromise blood flow…
Incorporation of Digital Implants Into CT Images to Plan Orthopedic Surgery
Orthopedic surgery addresses conditions of the musculoskeletal system to alleviate pain, restore function, and enhance the patient’s quality of life. Its success relies on meticulous pre-operative planning that incorporates clinical data and patient-specific imaging to…
Digital Health at the Top of the National Poliempreende 2024 Results
Poliempreende is a consolidated national network for encouraging entrepreneurship in higher education in Portugal, with two decades of existence. Focused on promoting innovation, the competition has had a significant impact on the national economy, with…
Digital Solution Facilitates Interaction Between Users and Health Professionals
Many patients face difficulties scheduling medical appointments in hospital units, and, when successful, they often endure long waiting times to be attended. This situation is aggravated by problems such as the incompatibility of schedules between…
The Impact of Calm Computing Integration on the Clinical Process
In recent years, digital transformation in healthcare has played a crucial role, driven by the exponential increase in medical data. This ranges from administrative information to detailed records of diagnoses, laboratory tests, medical images and…
ULS Almada-Seixal Revolutionizes With the Region’s First Surgical Robot
In recent years, ULSAS has been gradually implementing robotic systems, reinforcing its commitment to innovation and improving healthcare. Recently, the institution acquired a state-of-the-art robotic system, developed under the concept of an ‘immersive intuitive interface’,…
Online Intervention Aims to Prevent Anxiety in the General Population
Anxiety disorders are a global problem, affecting 300 million people worldwide and placing significant pressure on individuals and healthcare systems. In Europe alone, the economic impact reached 74.380 million in 2010, with 62.2% attributed to…
Rehabilitation of Facial Paralysis Through Virtual Assistants
Facial paralysis, defined by the inability to move one or both sides of the face, has an incidence of 20 to 30 cases per 100,000 people annually. This condition often causes facial weakness, difficulties in…
Detection of Anxiety and Panic Attacks in Real Time
The growing number of people with anxiety disorders, along with increased awareness of mental health, drives the need for new technological tools that provide remote and continuous monitoring of anxiety and panic disorders. Thus, the…
A Novel Approach for Robotic-assisted Tele-echography
Currently, robotic systems for ultrasound diagnostic procedures fall into two main categories: portable robots that require manual positioning and fully autonomous robotic systems that independently control the ultrasound probe’s orientation and positioning. Portable robots rely…
From Big Data to Big Decisions: How AI Stratifies Cancer Cases by Risk Factors
The CLARIFY Decision Support Platform (DSP) is a responsive web application designed to support decision-making in cancer care through real-time data integration and predictive analytics. Built on Big Data Europe, the platform integrates a variety…
From “Free Text” to Structured Clinical Data: the Foundation for Clinical Decision Support Systems
Currently, the practice of recording clinical information in “free text” offers flexibility, but hinders automatic data extraction, limiting the application of analytical models. Most records are unstructured, and the use of non-standard abbreviations increases ambiguity,…
Integration of SONHO v2 and SClínico Systems at ULS of Coimbra to Improve Healthcare Services
With more than half a million hospital medical consultations carried out in the first half of 2024, the ULS of Coimbra stands out as an institution dedicated to integrated, high-quality and patient-centered healthcare, with 8…
Elderly Care Ecosystem: an Innovative Platform for Personalized and Efficient Services
The Elderly Care Ecosystem (ECE) is an integration of various digital health technologies, exploring the areas of telehealth and predictive analytics. The goal of this ecosystem is to improve the quality of life for elderly…
Innovative technology that subconsciously relieves anxiety through a scarf
The SCAARF technology aims to offer an alternative method to alleviate anxiety symptoms in a non-intrusive and subconscious way. This technology is an innovative idea in the field of digital health and wearable technology, designed…
Digital Health Interventions: Equity in Hypertension Care for Everyone
Nearly half of all adults in the United States have hypertension, one of the leading risk factors for cardiovascular disease, and only about a quarter (24%) of those people have their hypertension under control. Studies…
Personalization and Technology in Diabetes Management
IPDM has significant potential to improve diabetes management and drive health system reforms to become high-performing, effective, equitable, accessible, and sustainable. Evidence and good practices inspire health system transformation. Adopting person-centred approaches like co-creation and…
Negotiations on the European Health Data Space Advance With the Participation of the SPMS
The European Health Data Space will be a common health data sharing system across the European Union. It foresees the use of data for purposes that benefit people and society. It will ensure citizens have…
Secretary of State Margarida Tavares Emphasizes Digital Innovation in Health Promotion
Margarida Tavares spoke at the opening of the conference ” O Digital na promoção contínua da saúde e do bem-estar”, organized by the Associação para a Promoção e Desenvolvimento da Sociedade da Informação (APDSI) and…
ARS Algarve Modernizes Radiology With AI and New Data Center
The radiology service of ARS Algarve has already performed nearly 29,000 exams using Artificial Intelligence (AI) technology. In recent years, there has been a significant investment in image digitization and data storage, as well as…
European Health Data Space: Unified Access To Health Data In The EU
The COVID-19 pandemic highlighted the importance of digital services in health, but complex rules and increasing cyberattacks make it difficult to share data across Member States; the EHDS, based on several regulations, provides tailor-made rules…
European Commission Amends Digital Europe Programme With an Investment of €762.7 Million
The European Commission has amended the Digital Europe Programme work programmes 2023-2024, investing an additional €762.7 million in Europe’s digital transition and cybersecurity. The digital transition is the main work programme with a budget of…
SPMS Integrates the TEF-Health Initiative
SPMS participates in the TEF-Health initiative as a partner in a consortium composed of 51 entities from 9 European Union countries. This action is co-financed by the European Commission and has a duration of five…
FMUP Creates Inhealth Junior Academy for High School Students
The InHealth Junior Academy — Academia Júnior de Inovação em Saúde is an initiative of the Departamento de Medicina da Comunidade, Informação e Decisão em Saúde da Faculdade de Medicina da Universidade do Porto (FMUP)….
SPMS Represents Portugal as Vice-president of GDHP
The GDHP is an intergovernmental organization in the digital health sector that facilitates cooperation and collaboration between government representatives and the World Health Organization (WHO). Its purpose is to foster policymaking that promote the digitalization…
Digital Transformation of Health at INCoDe.2030 in Tomar
The “National Digital Skills Initiative e.2030, Portugal” (INCoDe.2030) is an initiative that aims to improve the Portuguese population’s level of digital skills, placing Portugal at the level of the most advanced European countries in this…
Braga Hospital Evaluates Memory With Interactive Game in Patients With Multiple Sclerosis
Multiple Sclerosis is known as a chronic disease of the central nervous system, with a wide variety of motor and sensory symptoms that can lead to work disability, socioeconomic burden, and reduced quality of life…
Neurosurgery Teleconsultation Wins Innovation Award
The aim of the BI Award for Innovation in Healthcare is to recognize innovative projects in the healthcare sector that improve the quality of life for the Portuguese people. In 2021, the specific theme was…
HealthData@PT: New SPMS Initiative for Health Data
Action HealthData@PT is launched in the context of the implementation of the European Health Data Space, and is an initiative approved by the European Commission under the EU4Health 2021-2027 programme. This initiative contributes to the…
Do you have an innovative idea in healthcare field?
Share it with us and see it come to life.
We will help bring your projects to life!