AIMC Topic: Humans

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AI-MK: artificial intelligence for assessing and monitoring microbial keratitis.

BMJ open ophthalmology
BACKGROUND/AIMS: To evaluate the performance of an artificial intelligence (AI) model for detecting and monitoring microbial keratitis (MK) using anterior segment optical coherence tomography (AS-OCT).

Evaluating the Efficacy of AI-Based Interactive Assessments Using Large Language Models for Depression Screening: Development and Usability Study.

JMIR formative research
BACKGROUND: The evolution of language models, particularly large language models, has introduced transformative potential for psychological assessment, challenging traditional rating scale methods that have dominated clinical practice for over a cent...

Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With Hypertension: Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: Hypertension remains a major global health challenge, significantly increasing cardiovascular and all-cause mortality risks. While exercise therapy is effective, conventional approaches face limitations in accessibility and personalizatio...

Bridging Gaps in Women's Heart Health: User-Centered Needs Assessment Informed by Patient and Clinician Interviews.

JMIR human factors
BACKGROUND: Women with cardiovascular disease (CVD) remain underserved due to gaps in recognition, diagnosis, and care tailored to sex-specific risks. Digital health tools have the potential to address these inequities, but many fail to reflect the d...

Explainable AI for Predicting Mortality Risk in Metastatic Cancer: Retrospective Cohort Study Using the Memorial Sloan Kettering-Metastatic Dataset.

JMIR cancer
BACKGROUND: Metastatic cancer remains one of the leading causes of cancer-related mortality worldwide. Yet, the prediction of survivability in this population remains limited by heterogeneous clinical presentations and high-dimensional molecular feat...

Neutrophil Percentage-to-Albumin Ratio as a Novel Prognostic Biomarker in Adult Diffuse Gliomas: Retrospective Study Integrating 3 Machine Learning Models and Cox Regression.

JMIR medical informatics
BACKGROUND: Adult-type diffuse glioma (ADG) is the most common primary malignant tumor of the central nervous system. Its highly invasive nature, marked heterogeneity, and resistance to therapy contribute to a high risk of recurrence and poor prognos...

Assessment of the Diagnostic Performance and Clinical Impact of AI in Hepatic Steatosis: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: The global rise of metabolic associated fatty liver disease reflects the urgent need for accurate, noninvasive diagnostic approaches. The invasive nature of liver biopsy and the limited sensitivity of ultrasound in detecting early steatos...

From glycolytic signatures to patients: A translational roadmap for reproducible, equitable deployment of multi-omics and AI in colorectal cancer.

Medical oncology (Northwood, London, England)
Recent advances in Medical Oncology highlight the integration of bulk and single-cell transcriptomics to reveal glycolytic heterogeneity in colorectal cancer. Translating these discoveries into reliable clinical tools requires rigorous methods, trans...

Environment and CVD: moving from Risk Prediction to Risk Management.

Current atherosclerosis reports
PURPOSE OF REVIEW: We attempt to provide a framework for cardiovascular risk assessment related to environmental pollutants to enhance awareness of risk posed by environmental risk factors and highlight approaches for risk intervention.

Development of an explainable prediction model for the risk of moderate-to-severe obstructive sleep apnea in children.

European journal of pediatrics
UNLABELLED: Early identification of children at high risk for moderate-to-severe obstructive sleep apnea (OSA) is crucial for timely intervention, yet is often hindered by limited access to polysomnography (PSG). We aimed to develop an interpretable ...