Risk Management

Structure-Based Prediction of QT Prolongation Risk Using Graph Neural Networks: An Integrative Approach Combining In Vitro hERG Assays and Pharmacovigilance Data.

Drug-induced QT-interval prolongation, a non-specific biomarker of increased risk for Torsades de Pointes (TdP), is a major safety concern in drug development. While in vitro hERG inhibition assays are required for early-phase screening, pharmacovigilance data from sources like the FDA Adverse Event Reporting System (FAERS) provide complementary insights. Integrating these heterogeneous data with ...

Protocol for non-invasive tumor monitoring and diagnosis based on interpretable deep learning.

Tumor-specific DNA methylation profiling in plasma cell-free DNA (cfDNA) offers a promising approach for non-invasive tumor detection. Here, we present a protocol that uses Oncoder, an interpretable deep-learning-based framework, to monitor treatment response by tracking dynamic changes in tumor-specific DNA methylation signals in patient plasma cfDNA. We describe steps for data preparation, perfo...

Malpractice in the machine age: Legal and ethical responses to machine learning in medical imaging.

OBJECTIVES: Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into diagnostic imaging. This review examines how AI ad...

Multi-omics profiling of chronic immune-mediated skin diseases: SKINERGY protocol and strategic evaluation.

BACKGROUND: The Dutch flagship project Next Generation ImmunoDermatology (NGID) aims to profile five chronic immune-mediated inflammatory skin disease...

Deep phenotyping of suicidal ideation after discharge from psychiatric inpatient care: study protocol for an interdisciplinary, multicentre prospective observational study in Psychiatric University Hospitals.

INTRODUCTION: Suicidal thoughts and behaviours (STB) are a critical public health concern, with 700 000 deaths by suicide each year. The period immedi...

Assessing Healthcare Professionals' Attitudes Toward Artificial Intelligence in Turkey: A Cross-Sectional Study.

OBJECTIVES: To assess healthcare professionals' attitudes toward artificial intelligence (AI) in healthcare and to identify personal and professional ...

Evaluating guideline adherence in LLM studies using LLMs.

PURPOSE: To evaluate the capability of large language models (LLM), specifically GPT-4 and o1, in assessing adherence to the MI-CLEAR-LLM checklist in...

Exploring Clinician Perspectives on Artificial Intelligence in Primary Care: Qualitative Systematic Review and Meta-Synthesis.

BACKGROUND: Recent advances have highlighted the potential of artificial intelligence (AI) systems to assist clinicians with administrative and clinic...

Improving the management and outcomes of preschool wheeze: protocol of a prospective multicentre cohort study.

INTRODUCTION: Preschool wheeze and asthma are associated with substantial morbidity and impaired future lung function. Yet, wheeze is unreliably repor...

Using Smartphone-Based Digital Phenotyping to Predict Relapse in Serious Mental Disorders Among Slum Residents in Dhaka, Bangladesh: Protocol for a Machine Learning Study.

BACKGROUND: Serious mental illnesses (SMIs) are associated with high relapse rates and limited access to continuous care, particularly in low-resource...

Artificial Intelligence-Assisted Detection of Amyloid-Related Imaging Abnormalities: Promise and Pitfalls.

The advent of anti-amyloid therapies (AATs) for Alzheimer disease (AD) has elevated the importance of MRI surveillance for amyloid-related imaging abn...

Machine learning-based COVID-19 prognostic models lag behind in reporting quality: findings from a TRIPOD/TRIPOD + AI systematic review.

BACKGROUND: Reporting of COVID-19 prognostic models frequently falls short of established standards. The TRIPOD checklist and its 2024 AI extension (T...

Using AI Algorithms and Machine Learning in the Analysis of a Bio-Purification Method (Therapeutic Emesis, Known as "Vamana Karma"): Protocol for a Mixed Methods Study.

BACKGROUND: Therapeutic emesis (TE), known as vamana karma, is a classical method of detoxification performed to eliminate vitiated kapha (bio-humor g...

Association and Agreement of Contact-Based Smartphone Photoplethysmography Compared With Electrocardiography: Protocol for a Systematic Review and Meta-Analysis.

BACKGROUND: Mobile health (mHealth), leveraging mobile devices for health measurement and promotion, is rapidly growing. Smartphone cameras can perfor...

Treating autism with Bumetanide: Identification of responders using Q-Finder machine learning algorithm.

Bumetanide, a specific NKCC1 co-transporter inhibitor, restores deficient GABAergic inhibition implicated in various brain disorders, including Autism...

Predicting adverse events for risk stratification of chemotherapy based stem cell mobilization in multiple myeloma.

Autologous stem-cell transplantation is a fundamental therapy for multiple myeloma. Although inpatient chemo-based stem-cell mobilization (SCM) is sta...

Energy-efficient intrusion detection with a protocol-aware transformer-spiking hybrid model.

Recent intrusion detection studies have achieved high accuracy using deep learning and transformer-based models; however, many approaches suffer from ...

Study design for an emulated trial of a 2 arm, parallel, stratified, adaptive, RCT of CABG versus PCI in people requiring myocardial revascularization at high risk (High-Risk REVASC).

AIM: This study aims to use routinely collected health data and trial emulation methodology to inform the design of a pragmatic randomized controlled ...

Explainable AI in Cardiology Diagnostics: A Systematic Review of Machine Learning, Meta-heuristic Optimization, and Clinical Text Mining for Coronary Artery Disease.

BACKGROUND: This systematic review compiles evidence and examines how various artificial intelligence (AI) approaches, including machine learning (ML)...

Developing a Multimodal Screening Algorithm for Mild Cognitive Impairment and Early Dementia in Home Health Care: Protocol for a Cross-Sectional Case-Control Study Using Speech Analysis, Large Language Models, and Electronic Health Records.

BACKGROUND: Mild cognitive impairment and early dementia (MCI-ED) are frequently unrecognized in routine care, particularly in home health care (HHC),...