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Prediction of pulmonary embolism by an explainable machine learning approach in the real world.
Scientific reports
Jan 4, 2025
In recent years, large amounts of researches showed that pulmonary embolism (PE) has become a common disease, and PE remains a clinical challenge because of its high mortality, high disability, high missed and high misdiagnosed rates. To address this...
Preoperative prediction of the selection of the NOTES approach for patients with symptomatic simple renal cysts via an interpretable machine learning model: a retrospective study of 264 patients.
Langenbeck's archives of surgery
Jan 4, 2025
BACKGROUND: There are multiple surgical approaches for treating symptomatic simple renal cysts (SSRCs). The natural orifice transluminal endoscopic surgery (NOTES) approach has gradually been applied as an emerging minimally invasive approach for the...
Assessing the feasibility and external validity of natural language processing-extracted data for advanced lung cancer patients.
Lung cancer (Amsterdam, Netherlands)
Jan 4, 2025
BACKGROUND: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with ad...
Exploring the potential of machine learning models to predict nasal measurements through facial landmarks.
The Journal of prosthetic dentistry
Jan 3, 2025
STATEMENT OF PROBLEM: Information on predicting the measurements of the nose from selected facial landmarks to assist in maxillofacial prosthodontics is lacking.
Predicting intermediate-risk prostate cancer using machine learning.
International urology and nephrology
Jan 3, 2025
PURPOSES: Intermediate-risk prostate cancer (IR PCa) is the most common risk group for localized prostate cancer. This study aimed to develop a machine learning (ML) model that utilizes biopsy predictors to estimate the probability of IR PCa and asse...
Finding Predictive Factors of Stabilization Exercise Adherence in Randomized Controlled Trials on Low Back Pain: An Individual Data Reanalysis Using Machine Learning Techniques.
Archives of physical medicine and rehabilitation
Jan 3, 2025
OBJECTIVE: To identify predictors of adherence in supervised and self-administered exercise interventions for individuals with low back pain.
Classification of Irritable Bowel Syndrome Using Brain Functional Connectivity Strength and Machine Learning.
Neurogastroenterology and motility
Jan 3, 2025
BACKGROUND: Irritable Bowel Syndrome (IBS) is a prevalent condition characterized by dysregulated brain-gut interactions. Despite its widespread impact, the brain mechanism of IBS remains incompletely understood, and there is a lack of objective diag...
A Longitudinal Prediction of Suicide Attempts in Borderline Personality Disorder: A Machine Learning Study.
Journal of clinical psychology
Jan 3, 2025
Borderline personality disorder (BPD) is associated with a high risk of suicide. Despite several risk factors being known, identifying vulnerable patients in clinical practice remains a challenge so far. The current study aimed at predicting suicide ...
The use of machine learning for the prediction of response to follow-up in spine registries.
International journal of medical informatics
Jan 3, 2025
BACKGROUND: One of the main challenges in the maintenance of registries is to keep a high follow-up rate and a reliable strategy to limit dropout is currently lacking. Aim of this study was to utilize machine learning (ML) models to highlight the cha...
The Adelaide Score: prospective implementation of an artificial intelligence system to improve hospital and cost efficiency.
ANZ journal of surgery
Jan 3, 2025
BACKGROUND: The Adelaide Score is an artificial intelligence system that integrates objective vital signs and laboratory tests to predict likelihood of hospital discharge.
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