AIMC Topic: Female

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Evaluation of Machine Learning Model Performance in Diabetic Foot Ulcer: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Machine learning (ML) has shown great potential in recognizing complex disease patterns and supporting clinical decision-making. Diabetic foot ulcers (DFUs) represent a significant multifactorial medical problem with high incidence and se...

Optimizing Loop Diuretic Treatment for Mortality Reduction in Patients With Acute Dyspnea Using a Practical Offline Reinforcement Learning Pipeline for Health Care: Retrospective Single-Center Simulation Study.

JMIR medical informatics
BACKGROUND: Offline reinforcement learning (RL) has been increasingly applied to clinical decision-making problems. However, due to the lack of a standardized pipeline, prior work often relied on strategies that may lead to overfitted policies and in...

Iloprost therapy achieves good clinical and radiological short and mid-term outcomes in patients with idiopathic aseptic osteonecrosis of the knee joint also in ARCO level II.

Archives of orthopaedic and trauma surgery
AIMS: The aim of this retrospective study was the evaluation of the patient-reported and radiological outcome of intravenous Iloprost therapy in the treatment of spontaneous osteonecrosis of the knee (SONK).

Clinical, biochemical, and molecular characterization of a cohort of Egyptian patients with Sanfilippo B syndrome (MPS IIIB): Bayesian Gaussian mixture model.

Molecular biology reports
BACKGROUND: Lysosomal storage diseases (LSDs) are a group of genetically heterogeneous inherited metabolic disorders that affect the functions of the lysosomes in different human tissues. Mucopolysaccharidosis IIIB (MPS IIIB), Sanfilippo B syndrome, ...

Machine Learning-Based Pathomics Signature for Perineural Invasion in Colorectal Cancer.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Perineural invasion (PNI) is strongly associated with poor clinical outcomes in colorectal cancer (CRC). However, no machine learning diagnostic model based on pathomics has been established for PNI detection in CRC. To address this issue,...

Performance of several large language models when answering common patient questions about type 1 diabetes in children: accuracy, comprehensibility and practicality.

BMC pediatrics
BACKGROUND: The use of large language models (LLMs) in healthcare has expanded significantly with advances in natural language processing. Models, such as ChatGPT and Google Gemini, are increasingly used to generate human-like responses to questions,...

Real-Time Identification of Cricothyrotomy Landmarks in Emergency Care and Obstetric Patients Using Wireless Handheld Ultrasound and Edge-Computing Artificial Intelligence: A Prospective Observational Study.

Journal of medical systems
This study aimed to develop machine learning-based algorithms to assist physicians in ultrasound-guided localization of the cricoid cartilage (CC), thyroid cartilage (TC), and cricothyroid membrane (CTM) for cricothyroidotomy. Adult female participan...

SHAP-enhanced machine learning identifies modifiable obesity predictors across adolescent weight groups: A 2021 YRBSS analysis.

PloS one
BACKGROUND: The growing prevalence of obesity in adolescents around the world poses a major threat to public health. This research uses machine learning models to examine the main causes of obesity, in contrast to standard information that typically ...

Development and internal validation of multimodal machine learning models for predicting eligibility for mechanical thrombectomy in suspected stroke patients using routinely collected clinical and imaging data.

PloS one
BACKGROUND: Mechanical thrombectomy (MT) eligibility for acute ischemic stroke (AIS) patients depends upon clinical and advanced imaging assessments like CT perfusion (CTP). Assessment complexities and limited access to advanced imaging investigation...