AI Medical Compendium

Leveraging large language models on free-text symptoms from participatory surveillance enhances pertussis forecasting in the United States.

BMC infectious diseases May 7, 2026

BACKGROUND: Declines in childhood vaccination in the U.S. have contributed to a resurgence of vaccine-preventable diseases, including a notable increase in pertussis cases. Traditional pertussis surveillance is limited by underdiagnosis and underrepo... read more

Hybrid model based on fuzzy logic and classification trees for the prediction of mortality of critical trauma patients: Pre-hospital variables from the RETRAUCI registry.

BMC medical research methodology May 7, 2026

BACKGROUND: In critically injured trauma patients, tools that stratify injury severity and estimate mortality are essential. Fuzzy logic (FL) enables the creation of accurate, interpretable models but requires decision rules, which can be generated u... read more

A multifeature machine learning and resting-state EEG study reveals differences in beta oscillation in late-life depression with or without mild cognitive impairment.

BMC psychiatry May 7, 2026

BACKGROUND: Late-life depression (LLD) often co-occurs with mild cognitive impairment (MCI), and patients with LLD and MCI (LLD-MCI) have an increased risk of progression to Alzheimer's disease (AD). However, differences in resting-state neural oscil... read more

Research on depression diagnosis method based on multi-scale analysis of frontal lead EEG.

BMC medical informatics and decision making May 7, 2026

BACKGROUND: Depression is one of the most prevalent mental disorders globally, severely affecting individuals' emotional, cognitive, and physical functions while imposing profound socioeconomic impacts. Traditional diagnostic approaches primarily rel... read more

Health AI research capacity and equity-adjusted patient value in 27 European Union countries: an ecological panel study, 2011-2024.

BMC public health May 7, 2026

BACKGROUND: Investments in health artificial intelligence (AI) are accelerating across European Union member states, yet evidence linking national AI research capacity to population-level health outcomes remains scarce. Most available evaluations foc... read more

Machine learning approaches to distinguish bipolar disorder from borderline personality disorder: a scoping review.

BMC psychiatry May 7, 2026

BACKGROUND: Borderline personality disorder (BPD) and bipolar disorder (BD) are debilitating psychiatric illnesses with significant rates of misdiagnosis. This scoping review explores the potential of machine learning (ML) approaches in distinguishin... read more

Smartphone-based lightweight AI system for real-time multiple anterior segment disease screening: development and real-world validation.

BMC medicine May 7, 2026

BACKGROUND: Anterior segment diseases are a major global cause of preventable blindness, especially in regions with limited access to specialized ophthalmic care. Diagnosis typically requires slit-lamp biomicroscopy, creating a significant access bot... read more

ZDHHC5: a pivotal palmitoyltransferase orchestrating signaling networks - unraveling mechanisms and therapeutic horizons.

Biomarker research May 7, 2026

ZDHHC5, a key member of the DHHC family of palmitoyltransferases, catalyzes S-acylation-a reversible post-translational modification involving the covalent attachment of fatty acids, typically palmitate, to specific cysteine residues on target protei... read more

The Ethics Committee of the Italian Society of Anesthesia, Analgesia, Resuscitation and Intensive Care (SIAARTI) - Artificial intelligence in end-of-life decision-making processes: ethical reflections.

Journal of anesthesia, analgesia and critical care May 7, 2026

Recent proposals to use artificial intelligence (AI) in end-of-life decision-making for incapacitated patients without advance directives have prompted critical reflection by the Ethics Committee of the Italian Society of Anesthesia, Analgesia, Resus... read more

Single-cell and machine learning-integrated bulk RNA-seq analysis reveals TKT as an oxidative stress-associated diagnostic biomarker in acute myocardial infarction.

Human genomics May 7, 2026

BACKGROUND: Acute myocardial infarction (AMI) is a leading cause of death worldwide, with oxidative stress (OS) playing a central role in its pathogenesis. However, the dynamic expression profiles and functional implications of OS-related genes at th... read more

Artificial Intelligence Medical Compendium