AIMC Topic: Humans

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NLP-ROPCare: predicting retinopathy of prematurity with admission notes using natural language processing.

BMJ open ophthalmology
OBJECTIVES: Retinopathy of prematurity (ROP) is a leading cause of blindness in children worldwide, requiring more efficient models to help predict treatment-requiring ROP. Our study aimed to develop a new prediction model for ROP occurrence and seve...

Development and external validation of machine learning approaches for risk prediction of cardiovascular disease in individuals with schizophrenia: a nationwide Swedish and Danish study.

BMJ mental health
BACKGROUND: Currently available cardiovascular disease (CVD) risk prediction tools may underestimate the risk in individuals with schizophrenia. OBJECTIVE: To develop and externally validate 5-year CVD risk prediction models for people with schizophr...

Barriers and facilitators to implementing the living guideline development framework in oncology: a mixed methods study.

BMJ open
OBJECTIVE: To explore stakeholder experiences with implementing the living guideline (LG) development framework in oncology, and to identify barriers, facilitators and solutions to support its uptake and sustainability. DESIGN: An exploratory sequent...

Development of Venous Thromboembolism Risk Prediction Models Based on Whole Blood Gene Expression Profiling Using 20 Machine Learning Algorithms: Comprehensive Analysis Study.

JMIR medical informatics
BACKGROUND: There is a lack of venous thromboembolism (VTE) risk prediction models based on gene expression information. OBJECTIVE: This study aimed to construct a VTE prediction model based on whole blood gene expression profiling, by performing a c...

Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review.

JMIR cancer
BACKGROUND: Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major factors include smoking, obesity, and hypertension, though its etiology is uncertain. While surgery...

How to Evaluate the Accuracy of Symptom Checkers and Diagnostic Decision Support Systems: Symptom Checker Accuracy Reporting Framework (SCARF).

JMIR human factors
Symptom checkers are apps and websites that assist medical laypeople in diagnosing their symptoms and determining which course of action to take. When evaluating these tools, previous studies primarily used an approach introduced a decade ago that la...

The Diagnostic Value of Image-Based Machine Learning for Osteoporosis: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Osteoporosis (OP) is projected to be a major issue significantly impacting the well-being of middle-aged and old populations. Machine learning (ML) and deep learning (DL) models developed based on medical imaging have enhanced clinicians'...

Insights Into Factors Affecting Nurses' Knowledge of and Attitudes Toward AI and Implications for Successful AI Integration in Critical Care: Cross-Sectional Study.

JMIR nursing
BACKGROUND: Assessing the current landscape of nurses' knowledge and attitudes is a critical first step in facilitating a smooth and effective transition toward artificial intelligence (AI)-enhanced critical care. OBJECTIVE: This study aimed to asses...

Data Science Education for Residents, Researchers, and Students in Psychiatry and Psychology: Program Development and Evaluation Study.

JMIR medical education
BACKGROUND: The use of artificial intelligence (AI) to analyze health care data has become common in behavioral health sciences. However, the lack of training opportunities for mental health professionals limits clinicians' ability to adopt AI in cli...

Multi-omics Mendelian randomization and machine learning identify candidate therapeutic targets for Alzheimer's and Parkinson's diseases.

Mammalian genome : official journal of the International Mammalian Genome Society
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are major public health challenges lacking effective therapies. To identify potential drug targets, we integrated large-scale genome-wide association ...