AIMC Topic: Male

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Machine learning-based identification and validation of aging-related genes in cardiomyocytes from patients with atrial fibrillation.

Minerva cardiology and angiology
BACKGROUND: Aging is a key risk factor for atrial fibrillation (AF), a prevalent cardiac disorder among the elderly. This study aims to elucidate the genetic underpinnings of AF in the context of aging.

Evaluating the positive predictive value of code-based identification of cirrhosis and its complications utilizing GPT-4.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Diagnosis code classification is a common method for cohort identification in cirrhosis research, but it is often inaccurate and augmented by labor-intensive chart review. Natural language processing using large language models (...

Evaluation of the accuracy of automated segmentation based on deep learning for prostate cancer patients.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists
PURPOSE: This study evaluated the accuracy of a commercial deep learning (DL)-based algorithm for segmenting the prostate, seminal vesicles (SV), and organs at risk (OAR) in patients with prostate cancer.

Predicting criminal offence in adolescents who exhibit antisocial behaviour: a machine learning study using data from a large randomised controlled trial of multisystemic therapy.

European child & adolescent psychiatry
INTRODUCTION: Accurate prediction of short-term offending in young people exhibiting antisocial behaviour could support targeted interventions. Here we develop a set of machine learning (ML) models that predict offending status with good accuracy; fu...

Development and validation of the PHM-CPA model to predict in-hospital mortality for cirrhotic patients with acute kidney injury.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: The presence of acute kidney injury (AKI) significantly increases in-hospital mortality risk for cirrhotic patients. Early prognosis prediction for these patients is crucial. We aimed to develop and validate a machine learning model for i...

GloGen: PPG prompts for few-shot transfer learning in blood pressure estimation.

Computers in biology and medicine
With the rapid advancements in machine learning, its applications in the medical field have garnered increasing interest, particularly in non-invasive health monitoring methods. Blood pressure (BP) estimation using Photoplethysmogram (PPG) signals pr...

Clinicopathological features for the prediction of immunosuppressive treatment responses in sarcoidosis-related kidney involvement: a single-center retrospective study.

Turkish journal of medical sciences
BACKGROUND/AIM: Sarcoidosis is a multisystem disorder that affects many organs, including the kidneys. This single-center retrospective study investigated the clinical, pathological, and laboratory findings of patients with kidney sarcoidosis who wer...

Advancing non-alcoholic fatty liver disease prediction: a comprehensive machine learning approach integrating SHAP interpretability and multi-cohort validation.

Frontiers in endocrinology
INTRODUCTION: Non-alcoholic fatty liver disease (NAFLD) represents a major global health challenge, often undiagnosed because of suboptimal screening tools. Advances in machine learning (ML) offer potential improvements in predictive diagnostics, lev...