AI Medical Compendium Topic:
Logistic Models

Clear Filters Showing 981 to 990 of 1140 articles

Using Machine Learning and Artificial Intelligence to Predict Diabetes Mellitus among Women Population.

Current diabetes reviews
BACKGROUND: Diabetes Mellitus is a chronic health condition (long-lasting) due to inadequate control of blood levels of glucose. This study presents a prediction of Type 2 Diabetes Mellitus among women using various Machine Learning Algorithms deploy...

Predicting apheresis yield and factors affecting peripheral blood stem cell harvesting using a machine learning model.

The Journal of international medical research
OBJECTIVE: Mobilization and collection of peripheral blood stem cells (PBSCs) are time-intensive and costly. Excessive apheresis sessions can cause physical discomfort for donors and increase the costs associated with collection. Therefore, it is ess...

[Construction and external validation of a non-invasive pre-hospital screening model for stroke patients: a study based on artificial intelligence DeepFM algorithm].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To construct a non-invasive pre-hospital screening model and early based on artificial intelligence algorithms to provide the severity of stroke in patients, provide screening, guidance and early warning for stroke patients and their famil...

Can machine learning models improve the prediction of surgical site infection in abdominal surgery than traditional statistical models?

The Journal of international medical research
OBJECTIVE: To externally validate by revision and update the study on the efficacy of nosocomial infection control (SENIC) model of surgical site infection (SSI) using logistic regression (LR) and machine learning (ML) approaches.

Clinical utility of an artificial intelligence radiomics-based tool for risk stratification of pulmonary nodules.

JNCI cancer spectrum
BACKGROUND: Clinical utility data on pulmonary nodule (PN) risk stratification biomarkers are lacking. We aimed to determine the incremental predictive value and clinical utility of using an artificial intelligence (AI) radiomics-based computer-aided...

Machine Learning-Based Prediction of Hemoglobinopathies Using Complete Blood Count Data.

Clinical chemistry
BACKGROUND: Hemoglobinopathies, the most common inherited blood disorder, are frequently underdiagnosed. Early identification of carriers is important for genetic counseling of couples at risk. The aim of this study was to develop and validate a nove...

Research on predicting hematoma expansion in spontaneous intracerebral hemorrhage based on deep features of the VGG-19 network.

Postgraduate medical journal
PURPOSE: To construct a clinical noncontrastive computed tomography (NCCT) deep learning joint model for predicting early hematoma expansion (HE) after cerebral hemorrhage (sICH) and evaluate its predictive performance.

Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Leverage electronic health record (EHR) audit logs to develop a machine learning (ML) model that predicts which notes a clinician wants to review when seeing oncology patients.

Comparing the accuracy of four machine learning models in predicting type 2 diabetes onset within the Chinese population: a retrospective study.

The Journal of international medical research
OBJECTIVE: To evaluate the effectiveness of machine learning (ML) models in predicting 5-year type 2 diabetes mellitus (T2DM) risk within the Chinese population by retrospectively analyzing annual health checkup records.

Machine learning trial to detect sex differences in simple sticker arts of 1606 preschool children.

Minerva pediatrics
BACKGROUND: Previous studies suggested that drawings made by preschool boys and girls show distinguishable differences. However, children's drawings on their own are too complexly determined and inherently ambiguous to be a reliable indicator. In the...