AIMC Topic: Humans

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The Feasibility of Large Language Models in Verbal Comprehension Assessment: Mixed Methods Feasibility Study.

JMIR formative research
BACKGROUND: Cognitive assessment is an important component of applied psychology, but limited access and high costs make these evaluations challenging.

Machine Learning-Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study.

Journal of medical Internet research
BACKGROUND: To address gaps in global understanding of cultural and social variations, this study used a high-performance machine learning (ML) model to predict adolescent substance use across three national datasets.

Identifying Patient-Reported Care Experiences in Free-Text Survey Comments: Topic Modeling Study.

JMIR medical informatics
BACKGROUND: Patient-reported experience surveys allow administrators, clinicians, and researchers to quantify and improve health care by receiving feedback directly from patients. Existing research has focused primarily on quantitative analysis of su...

Artificial Intelligence in Andrology: A New Frontier in Male Infertility Diagnosis and Treatment.

Current urology reports
PURPOSE OF REVIEW: Infertility affects approximately 15% of couples globally, with male-factor infertility contributing to about half of these cases. Despite advancements in reproductive medicine, particularly in surgical methods, the prevalence of m...

Electroencephalogram (EEG) Based Fuzzy Logic and Spiking Neural Networks (FLSNN) for Advanced Multiple Neurological Disorder Diagnosis.

Brain topography
Neurological disorders are a major global health concern that have a substantial impact on death rates and quality of life. accurately identifying a number of diseases Due to inherent data uncertainties and Electroencephalogram (EEG) pattern overlap,...

Predictive modeling with linear machine learning can estimate glioblastoma survival in months based solely on MGMT-methylation status, age and sex.

Acta neurochirurgica
PURPOSE: Machine Learning (ML) has become an essential tool for analyzing biomedical data, facilitating the prediction of treatment outcomes and patient survival. However, the effectiveness of ML models heavily relies on both the choice of algorithms...

Building Trust with AI: How Essential is Validating AI Models in the Therapeutic Triad of Therapist, Patient, and Artificial Third? Comment on What is the Current and Future Status of Digital Mental Health Interventions?

The Spanish journal of psychology
Since the publication of "What is the Current and Future Status of Digital Mental Health Interventions?" the exponential growth and widespread adoption of ChatGPT have underscored the importance of reassessing its utility in digital mental health int...

A systematic review of machine learning-based prognostic models for acute pancreatitis: Towards improving methods and reporting quality.

PLoS medicine
BACKGROUND: An accurate prognostic tool is essential to aid clinical decision-making (e.g., patient triage) and to advance personalized medicine. However, such a prognostic tool is lacking for acute pancreatitis (AP). Increasingly machine learning (M...

Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia.

Frontiers in immunology
BACKGROUND: Neutrophil extracellular traps (NETs) play pivotal roles in various pathological processes. The formation of NETs is impaired in acute myeloid leukemia (AML), which can result in immunodeficiency and increased susceptibility to infection.

Comparative analysis prediction of prostate and testicular cancer mortality using machine learning: accuracy study.

Sao Paulo medical journal = Revista paulista de medicina
BACKGROUND: The mortality rates of prostate and testicular cancer are higher mortality in the northeast region.