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Ethics and governance of artificial intelligence for health: Guidance on large multi-modal models
Large multi-modal models (LMMs) are a fast-growing type of generative AI that can take in different types of data, such as text, images and video, and produce varied responses. The World Health Organization (WHO) has issued guidance on their use in health, with over 40 recommendations for governments, technology companies and healthcare providers. The guidance…
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AI-based diabetes care: risk prediction models and implementation concerns
AI is increasingly being used to predict a person’s risk of developing type 2 diabetes, which could help delay or prevent the disease through earlier, more personalised prevention. This editorial discusses a scoping review of 40 studies on AI models for diabetes risk prediction. It found that models combining electronic health records with other types…
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The Role of Gender: Gender Fairness in the Detection of Depression Symptoms on Social Media
The study found that the BDI-Sen dataset used for depression symptom detection on social media exhibits gender bias, with machine learning models such as mentalBERT showing predictive disparities that generally favour male users. Although bias mitigation techniques like data augmentation reduced the bias, they did not eliminate it completely. The existence of this bias affects…
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Gender Bias in AI’s Perception of Cardiovascular Risk
The study investigated gender bias in GPT-4’s assessment of coronary artery disease risk and showed that there was a substantial shift in the perception of risk between men and women when a psychiatric comorbidity was added to the vignette, even when they presented identical complaints. This resulted in women being assessed as having lower risk…
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Fairness in AI-Based Mental Health: Clinician Perspectives and Bias Mitigation
Considering how there is limited research on fairness in automated decision making systems in the clinical domain, particularly in the mental health domain, this study explores clinicians’ perceptions of AI fairness through two distinct scenarios: violence risk assessment and depression phenotype recognition using textual clinical notes. Clinicians were engaged with through semi-structured interviews to understand…
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Multimodal Fusion of EEG and Audio Spectrogram for Major Depressive Disorder Recognition Using Modified DenseNet121
Depression and anxiety are common, often co-occurring mental health disorders that complicate diagnosis due to overlapping symptoms and reliance on subjective assessments. Standard diagnostic tools are widely used but can introduce bias, as they depend on self-reported symptoms and clinician interpretation, which vary across individuals. These methods also fail to account for neurobiological factors such…
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Deconstructing demographic bias in speech-based machine learning models for digital health
This study explores gender and race bias in machine learning models that use speech to detect mental health outcomes, namely anxiety and depression. The authors examined where bias can come from, both in the acoustic features extracted from speech and in the labels used to train the models, as well as in the models’ decisions.…
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Racial bias in AI-mediated psychiatric diagnosis and treatment: a qualitative comparison of four large language models
The article investigates racial bias in psychiatric diagnosis and treatment recommendations across four large language models (LLMs): Claude, ChatGPT, Gemini, and NewMes-15. The study evaluates the models’ responses to ten psychiatric cases representing five diagnoses (depression, anxiety, schizophrenia, eating disorders, and ADHD) under three conditions: race-neutral, race-implied, and race-explicitly stated (African American). Key…
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Key language markers of depression on social media depend on race
A recent U.S. study published in PNAS found that artificial intelligence models analyzing social media posts can detect signs of depression in white Americans but are far less accurate for Black Americans, underscoring the dangers of using AI trained on non-diverse data in healthcare. According to co-author Sharath Chandra Guntuku from Penn Medicine, these differences…
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Artificial Intelligence in mental health and the biases of language based models
In this literature review of the uses of Natural Language Processing (NLP) models in psychiatry, an approach that “systematically evaluates each stage of model development to explore how biases arise from a clinical, data science and linguistic perspective” was employed to find existing patterns. The result was that significant biases were found, with respect to…
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Genetic correlation, pleiotropic loci and shared risk genes between major depressive disorder and gastrointestinal tract disorders
Although depression is often linked to digestive disorders, the biological connection behind this phenomenon has remained unclear. A recent genome-wide association study analyzed genetic data from hundreds of thousands of people to explore potential links between major depressive disorder (MDD) and gastrointestinal conditions such as peptic ulcers (mainly caused by H. pylori infection), acid reflux,…
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Neuropsychological Disorders, Seniors and Fundamental Rights
Proposal: Strategic Litigation to Address Seniors Rights in European Union Proposed Implementation: 2025 to 2027 Call: CERV-2024-CHAR-LITI – Promote civil society organisations’ awareness of, capacity building and implementation of the EU Charter of Fundamental Rights Proposed Budget: 508 057,40€ Keywords: Strategic Litigation, Seniors, Neuropsychological disorders, Dementia, civil society organizations, capacity building, legal professionals and practitioners,…
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Children’s Mental Health Literacy
Proposal: Empowering Children with Mental Health Literacy Online Proposed Implementation: 2025 to 2027 Call: CERV-2024-CHILD – Rights of the child and children’s participation Proposed Budget: 339 427,14€ Keywords: Mental Health, Raising awareness of children and/or young people Objective: The project aims to address the pressing issue of mental health among adolescents aged 14-17 in the…
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AEQUITAS
Proposal: Preparation of the CSOs and public healthcare sector to address gender and racial biases that might arise from the wide usage of AI in order to protect and promote fundamental rights Implementation: 2025 to 2027 Call: CERV-2024-CHAR-LITI – Promote civil society organizations’ awareness of, capacity building and implementation of the EU Charter of Fundamental…
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Association of Helicobacter pylori Infection with Depression and Anxiety: A Systematic Review and Meta-Analysis
The association between Helicobacter pylori infection and depression and anxiety has been reported in the literature. A meta-analysis was developed in 2024 with the aim of investigating the association between H. pylori infection with these mental health conditions. The systematic search was conducted not only in international sources such as PubMed, Web of Science, and…
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Impact of Helicobacter pylori eradication on age‑specific risk of incident dementia in patients with peptic ulcer disease: a nationwide population‑based cohort study
A large South Korean cohort study from 2024 examined whether peptic ulcer disease (PUD) and Helicobacter pylori eradication therapy influence dementia risk in adults aged 55–79. Using national health insurance data from 2002–2015 and propensity score matching, researchers assessed overall dementia and Alzheimer’s disease (AD) over 5–10 years. While the researchers did not directly verify…
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Enhance Antimicrobial Resistance Diagnostic Methods
Proposal: Genetic Biomarkers and Bioactive Compounds (from Plants, Bacteria, and Fungi): Enhancing Diagnostic Methods with Innovative Solutions in Healthcare Settings Related to the Growing Enhance Antimicrobial Resistance Proposed Implementation: 2025 to 2029 Call: HORIZON-HLTH-2024-DISEASE-09 – Partnerships in Health 2024 Proposed Budget: 36 862 500,00€ Keywords: Antimicrobial resistance, Antimicrobials, Bacteria, Fungi, Health determinants, Pathogen agents, Genetic…
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Predicting Environmental Impact on Healthm
Proposal: Predicting and Informing Air and Noise Pollution and Their Impact on Health from Environmental Data Proposed Implementation: 2025 to 2030 Call: HORIZON-MISS-2024-CIT-01- Changing urban spaces and mindsets to accelerate the transition to climate neutrality Proposed Budget: 4 998 382,50€ Keywords: Environmental health Objective: The project aims to tackle the interconnected challenges of air…
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Bio-Med AI Summer School debates the role of AI in healthcare
In September 2024, the National Library of Portugal in Lisbon hosted the Bio-Med AI Summer School, a three-day international event on the role of artificial intelligence in healthcare. Organised by whatnext.law, a research centre of NOVA School of Law and Vieira de Almeida, in partnership with the Biomedical Research Foundation of the Academy of Athens,…
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Investigating the synergistic effects of amitriptyline and H. pylori eradication on depressive-like behaviors and inflammatory cytokines in mice
Recent research has highlighted the potential role of Helicobacter pylori in the pathogenesis of psychiatric disorders. In this experimental study, researchers used mice to explore whether combining amitriptyline with H. pylori eradication therapy produced greater benefits than either treatment alone. Male mice were firstly allocated into four groups: healthy controls, H. pylori-infected mice, mice receiving…
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The Psychotic Impact of Helicobacter pylori Gastritis and Functional Dyspepsia on Depression: A Systematic Review
The clinical practice of adding antidepressant drugs to the therapy for the eradication of Helicobacter pylori, in addition to the standard drug regimen, has been widely considered in recent years but its specific role in this treatment is still unclear. In this systematic review researchers tried to establish if there is an association between H.…
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Psychological effects of Helicobacter pylori-associated atrophic gastritis in patients under 50 years: A cross-sectional study
A cross-sectional, observational study involving 975 Japanese individuals who underwent a health checkup, has found that people with atrophic gastritis had a significantly higher risk of experiencing psychological distress or depressed mood. Interestingly, the risk was higher in females under 50 years old, regardless of H. pylori infection status. Although the mechanism remains to be…
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Correlation between social factors and anxiety-depression in function dyspepsia: do relationships exist?
A research study conducted on the Chinese population in 2014 aimed at evaluating the prevalence and the social factors linked to anxiety and depression in patients with functional dyspepsia (FD). This study included 907 patients with FD who attended a gastroenterology service. Despite being a hospital-based study, results showed that patients with functional dyspepsia had…