AIMC Topic: Humans

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Machine learning-based plasma metabolomics for improved cirrhosis risk stratification.

BMC gastroenterology
BACKGROUND: Cirrhosis is a leading cause of mortality in patients with chronic liver disease (CLD). The rapid development of metabolomic technologies has enabled the capture of metabolic changes related to the progression of cirrhosis.

Integrating manual annotation with deep transfer learning and radiomics for vertebral fracture analysis.

BMC medical imaging
BACKGROUND: Vertebral compression fractures (VCFs) are prevalent in the elderly, often caused by osteoporosis or trauma. Differentiating acute from chronic VCFs is vital for treatment planning, but MRI, the gold standard, is inaccessible for some. Ho...

A foundation systematic review of natural language processing applied to gastroenterology & hepatology.

BMC gastroenterology
OBJECTIVE: This review assesses the progress of NLP in gastroenterology to date, grades the robustness of the methodology, exposes the field to a new generation of authors, and highlights opportunities for future research.

Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets.

Scientific reports
Diabetes Mellitus (DM) is a global health challenge, and accurate early detection is critical for effective management. The study explores the potential of machine learning for improved diabetes prediction using microarray gene expression data and PI...

Assessing the diagnostic accuracy of machine learning algorithms for identification of asthma in United States adults based on NHANES dataset.

Scientific reports
Asthma diagnosis poses challenges due to underreporting of symptoms, misdiagnoses, and limitations in existing diagnostic tests. Machine learning (ML) offers a promising avenue for addressing these challenges by leveraging demographic and clinical da...

Cross-sectional design and protocol for Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI).

BMJ open
INTRODUCTION: Artificial Intelligence Ready and Equitable for Diabetes Insights (AI-READI) is a data collection project on type 2 diabetes mellitus (T2DM) to facilitate the widespread use of artificial intelligence and machine learning (AI/ML) approa...

An Ontology for Digital Medicine Outcomes: Development of the Digital Medicine Outcomes Value Set (DOVeS).

JMIR medical informatics
BACKGROUND: Over the last 10-15 years, US health care and the practice of medicine itself have been transformed by a proliferation of digital medicine and digital therapeutic products (collectively, digital health tools [DHTs]). While a number of DHT...

Mapping and Summarizing the Research on AI Systems for Automating Medical History Taking and Triage: Scoping Review.

Journal of medical Internet research
BACKGROUND: The integration of artificial intelligence (AI) systems for automating medical history taking and triage can significantly enhance patient flow in health care systems. Despite the promising performance of numerous AI studies, only a limit...

ChatGPT-4 Performance on German Continuing Medical Education-Friend or Foe (Trick or Treat)? Protocol for a Randomized Controlled Trial.

JMIR research protocols
BACKGROUND: The increasing development and spread of artificial and assistive intelligence is opening up new areas of application not only in applied medicine but also in related fields such as continuing medical education (CME), which is part of the...

Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study.

Journal of medical Internet research
BACKGROUND: Mumps is a viral respiratory disease characterized by facial swelling and transmitted through respiratory secretions. Despite the availability of an effective vaccine, mumps outbreaks have reemerged globally, including in China, where it ...