AIMC Topic: Adolescent

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Stepwise Transfer Learning for Expert-level Pediatric Brain Tumor MRI Segmentation in a Limited Data Scenario.

Radiology. Artificial intelligence
Purpose To develop, externally test, and evaluate clinical acceptability of a deep learning pediatric brain tumor segmentation model using stepwise transfer learning. Materials and Methods In this retrospective study, the authors leveraged two T2-wei...

Understanding and predicting pregnancy termination in Bangladesh: A comprehensive analysis using a hybrid machine learning approach.

Medicine
Reproductive health issues, including unsafe pregnancy termination, remain a significant concern for women in developing nations. This study focused on investigating and predicting pregnancy termination in Bangladesh by employing a hybrid machine lea...

Application of machine learning in the preoperative radiomic diagnosis of ameloblastoma and odontogenic keratocyst based on cone-beam CT.

Dento maxillo facial radiology
OBJECTIVES: Preoperative diagnosis of oral ameloblastoma (AME) and odontogenic keratocyst (OKC) has been a challenge in dentistry. This study uses radiomics approaches and machine learning (ML) algorithms to characterize cone-beam CT (CBCT) image fea...

Unsupervised Machine Learning in Countermovement Jump and Isometric Mid-Thigh Pull Performance Produces Distinct Combat and Physical Fitness Clusters in Male and Female U.S. Marine Corps Recruits.

Military medicine
INTRODUCTION: Several challenges face the U.S. Marine Corps (USMC) and other services in their efforts to design recruit training to augment warfighter mobility and resilience in both male and female recruits as part of an integrated model. Strength ...

Quantification of follicles in human ovarian tissue using image processing software and trained artificial intelligence†.

Biology of reproduction
Cancer survival rates in prepubertal girls and young women have risen in recent decades due to increasingly efficient treatments. However, many such treatments are gonadotoxic, causing premature ovarian insufficiency, loss of fertility, and ovarian e...

Automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning.

Medicine
The aim of this study was to construct a classification model for the automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning. We retrospectively collected elbow joint Radiographs of children aged 3 to ...

National Implementation of an Artificial Intelligence-Based Virtual Dietitian for Patients With Cancer.

JCO clinical cancer informatics
PURPOSE: Nutritional status is an established driver of cancer outcomes, but there is an insufficient workforce of registered dietitians to meet patient needs for nutritional counseling. Artificial intelligence (AI) and machine learning (ML) afford t...

Predicting type 1 diabetes in children using electronic health records in primary care in the UK: development and validation of a machine-learning algorithm.

The Lancet. Digital health
BACKGROUND: Children presenting to primary care with suspected type 1 diabetes should be referred immediately to secondary care to avoid life-threatening diabetic ketoacidosis. However, early recognition of children with type 1 diabetes is challengin...