AIMC Topic: Logistic Models

Clear Filters Showing 391 to 400 of 1261 articles

Application of machine learning to predict postoperative gastrointestinal bleed in bariatric surgery.

Surgical endoscopy
BACKGROUND: Postoperative gastrointestinal bleeding (GIB) is a rare but serious complication of bariatric surgery. The recent rise in extended venous thromboembolism regimens as well as outpatient bariatric surgery may increase the risk of postoperat...

A forensic evaluation method for DeepFake detection using DCNN-based facial similarity scores.

Forensic science international
Detecting DeepFake videos has become a central task in modern multimedia forensics applications. This article presents a method to detect face swapped videos when the portrayed person in the video is known. We propose using a threshold classifier bas...

The Adelaide Score: An artificial intelligence measure of readiness for discharge after general surgery.

ANZ journal of surgery
BACKGROUND: This study aimed to examine the performance of machine learning algorithms for the prediction of discharge within 12 and 24 h to produce a measure of readiness for discharge after general surgery.

Deep learning generates custom-made logistic regression models for explaining how breast cancer subtypes are classified.

PloS one
Differentiating the intrinsic subtypes of breast cancer is crucial for deciding the best treatment strategy. Deep learning can predict the subtypes from genetic information more accurately than conventional statistical methods, but to date, deep lear...

A machine learning model for orthodontic extraction/non-extraction decision in a racially and ethnically diverse patient population.

International orthodontics
INTRODUCTION: The purpose of the present study was to create a machine learning (ML) algorithm with the ability to predict the extraction/non-extraction decision in a racially and ethnically diverse sample.

Older driver at-fault crashes at unsignalized intersections in Alabama: Injury severity analysis with supporting evidence from a deep learning based approach.

Journal of safety research
INTRODUCTION: The research described in this paper explored the factors contributing to the injury severity resulting from the male and female older driver (65 years and older) at-fault crashes at unsignalized intersections in Alabama.

Prevalence of depressive symptoms and associated factors during the COVID-19 pandemic: A national-based study.

Journal of affective disorders
BACKGROUND: Previous studies have reported that the prevalence of depression and depressive symptoms was significantly higher than that before the COVID-19 pandemic. This study aimed to explore the prevalence of depressive symptoms and evaluate the i...

The utility of machine learning for predicting donor discard in abdominal transplantation.

Clinical transplantation
BACKGROUND: Increasing access and better allocation of organs in the field of transplantation is a critical problem in clinical care. Limitations exist in accurately predicting allograft discard. Potential exists for machine learning to provide a bal...

Logistic regression technique is comparable to complex machine learning algorithms in predicting cognitive impairment related to post intensive care syndrome.

Scientific reports
To evaluate the performance of machine learning (ML) models and to compare it with logistic regression (LR) technique in predicting cognitive impairment related to post intensive care syndrome (PICS-CI). We conducted a prospective observational study...

Use of artificial neural networks in the prognosis of musculoskeletal diseases-a scoping review.

BMC musculoskeletal disorders
To determine the current evidence on artificial neural network (ANN) in prognostic studies of musculoskeletal diseases (MSD) and to assess the accuracy of ANN in predicting the prognosis of patients with MSD. The scoping review was reported under the...