AIMC Topic: Humans

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It takes one to know one-Machine learning for identifying OBGYN abstracts written by ChatGPT.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVES: To use machine learning to optimize the detection of obstetrics and gynecology (OBGYN) Chat Generative Pre-trained Transformer (ChatGPT) -written abstracts of all OBGYN journals.

Trust in Machine Learning Driven Clinical Decision Support Tools Among Otolaryngologists.

The Laryngoscope
BACKGROUND: Machine learning driven clinical decision support tools (ML-CDST) are on the verge of being integrated into clinical settings, including in Otolaryngology-Head & Neck Surgery. In this study, we investigated whether such CDST may influence...

Predicting Penicillin Allergy: A United States Multicenter Retrospective Study.

The journal of allergy and clinical immunology. In practice
BACKGROUND: Using the reaction history in logistic regression and machine learning (ML) models to predict penicillin allergy has been reported based on non-US data.

A Machine Learning Approach to Predict Post-stroke Fatigue. The Nor-COAST study.

Archives of physical medicine and rehabilitation
OBJECTIVE: This study aimed to predict fatigue 18 months post-stroke by utilizing comprehensive data from the acute and sub-acute phases after stroke in a machine-learning set-up.

Prediction of Disease-Free Survival in Breast Cancer using Deep Learning with Ultrasound and Mammography: A Multicenter Study.

Clinical breast cancer
BACKGROUND: Breast cancer is a leading cause of cancer morbility and mortality in women. The possibility of overtreatment or inappropriate treatment exists, and methods for evaluating prognosis need to be improved.

Automated pancreatic segmentation and fat fraction evaluation based on a self-supervised transfer learning network.

Computers in biology and medicine
Accurate segmentation of the pancreas from abdominal computed tomography (CT) images is challenging but essential for the diagnosis and treatment of pancreatic disorders such as tumours and diabetes. In this study, a dataset with 229 sets of high-res...

Towards federated transfer learning in electrocardiogram signal analysis.

Computers in biology and medicine
Modern methods in artificial intelligence perform very well on many healthcare datasets, at times outperforming trained doctors. However, many assumptions made in model training are not justifiable in clinical settings. In this work, we propose a met...

Automated scoring of the autobiographical interview with natural language processing.

Behavior research methods
The autobiographical interview has been used in more than 200 studies to assess the content of autobiographical memories. In a typical experiment, participants recall memories, which are then scored manually for internal details (episodic details fro...