AIMC Topic: Female

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The potential of evaluating shape drawing using machine learning for predicting high autistic traits.

PloS one
BACKGROUND: Children with high autistic traits often exhibit deficits in drawing, an important skill for social adaptability. Machine learning is a powerful technique for learning predictive models from movement data, so drawing processes and product...

Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated delirium.

PloS one
This study aimed to develop models for predicting the 30-day mortality of sepsis-associated delirium (SAD) by multiple machine learning (ML) algorithms. On the whole, a cohort of 3,197 SAD patients were collected from the Medical Information Mart for...

Diagnostic performance of attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy for detecting osteoarthritis and rheumatoid arthritis from blood serum.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Osteoarthritis (OA) and rheumatoid arthritis (RA) are the two most common rheumatic diseases worldwide, causing pain and disability. Both conditions are highly heterogeneous, and their onset occurs insidiously with non-specific symptoms, so they are ...

Diagnostic performance of radiomics models for preoperative prediction of microsatellite instability status in endometrial cancer: a systematic review and meta-analysis.

Abdominal radiology (New York)
PURPOSE: Microsatellite instability (MSI), caused by defects in mismatch repair (MMR) genes, serves as a critical molecular biomarker with therapeutic implications for endometrial cancer (EC). This study aims to assess the diagnostic performance of r...

A machine learning approach for type 2 diabetes diagnosis and prognosis using tailored heterogeneous feature subsets.

Medical & biological engineering & computing
Type 2 diabetes (T2D) is becoming one of the leading health problems in Western societies, diminishing quality of life and consuming a significant share of healthcare resources. This study presents machine learning models for T2D diagnosis and progno...

Cross-institutional validation of a polar map-free 3D deep learning model for obstructive coronary artery disease prediction using myocardial perfusion imaging: insights into generalizability and bias.

European journal of nuclear medicine and molecular imaging
PURPOSE: Deep learning (DL) models for predicting obstructive coronary artery disease (CAD) using myocardial perfusion imaging (MPI) have shown potential for enhancing diagnostic accuracy. However, their ability to maintain consistent performance acr...

Machine learning prediction of effective radiation doses in various computed tomography applications: a virtual human phantom study.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: In this work, it was aimed to employ machine learning (ML) algorithms to accurately forecast the radiation doses for phantoms while accounting for the most popular CT protocols.

Establishing a Validation Framework of Treatment Discontinuation in Claims Data Using Natural Language Processing and Electronic Health Records.

Clinical pharmacology and therapeutics
Measuring medication discontinuation in claims data primarily relies on the gaps between prescription fills, but such definitions are rarely validated. This study aimed to establish a natural language processing (NLP)-based validation framework to ev...

Development and validation of Prediction models for radiation-induced hypoglossal neuropathy in patients with nasopharyngeal carcinoma.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: To establish predictive models for radiation-induced hypoglossal neuropathy (RIHN) in patients with nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT).

Point-of-care ultrasound in obstetric anesthesia clinical practice.

Current opinion in anaesthesiology
PURPOSE OF THE REVIEW: Point-of-care ultrasound (POCUS) is increasingly recognized as a valuable tool in obstetric anesthesia. This review synthesizes key studies and reviews published within the last 2 years on its application in clinical practice w...