AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Adolescent

Showing 261 to 270 of 2960 articles

Clear Filters

Using Machine Learning to Predict Weight Gain in Adults: an Observational Analysis From the All of Us Research Program.

The Journal of surgical research
INTRODUCTION: Obesity, defined as a body mass index ≥30 kg/m, is a major public health concern in the United States. Preventative approaches are essential, but they are limited by an inability to accurately predict individuals at highest risk of weig...

Forecasting Pediatric Trauma Volumes: Insights From a Retrospective Study Using Machine Learning.

The Journal of surgical research
INTRODUCTION: Rising pediatric firearm-related fatalities in the United States strain Trauma Centers. Predicting trauma volume could improve resource management and preparedness, particularly if daily forecasts are achievable. The aim of the study is...

Comparison of the spatial and temporal distribution of cutaneous and mucosal leishmaniasis in the state of Rio de Janeiro between 2001 and 2011.

PloS one
OBJECTIVE: To compare the spatio-temporal distribution of cutaneous leishmaniasis (CL) cases with mucosal leishmaniasis (ML) cases in the state of Rio de Janeiro (RJ) between 2001 and 2011.

Prediction of prognosis in patients with cerebral contusions based on machine learning.

Scientific reports
Traumatic brain injury (TBI) is a global issue and a major cause of patient mortality, and cerebral contusions (CCs) is a common primary TBI. The haemorrhagic progression of a contusion (HPC) poses a significant risk to patients' lives, and effective...

Optimizing adult-oriented artificial intelligence for pediatric chest radiographs by adjusting operating points.

Scientific reports
The purpose of this study was to evaluate whether the optimal operating points of adult-oriented artificial intelligence (AI) software differ for pediatric chest radiographs and to assess its diagnostic performance. Chest radiographs from patients un...

Developing a fully applicable machine learning (ML) based sex classification model using linear cranial dimensions.

Scientific reports
Recent advances in artificial intelligence (AI) and machine learning (ML) applications have elevated accomplishments in various scientific fields, primarily those that benefit the economy and society. Contemporary threats, such as armed conflicts, na...

Limitations of panoramic radiographs in predicting mandibular wisdom tooth extraction and the potential of deep learning models to overcome them.

Scientific reports
Surgeons routinely interpret preoperative radiographic images for estimating the shape and position of the tooth prior to performing tooth extraction. In this study, we aimed to predict the difficulty of lower wisdom tooth extraction using only panor...

A machine learning tool for early identification of celiac disease autoimmunity.

Scientific reports
Identifying which patients should undergo serologic screening for celiac disease (CD) may help diagnose patients who otherwise often experience diagnostic delays or remain undiagnosed. Using anonymized outpatient data from the electronic medical reco...

Evaluation of the effectiveness of panoramic radiography in impacted mandibular third molars on deep learning models developed with findings obtained with cone beam computed tomography.

Oral radiology
OBJECTIVE: The aim of this study is to determine the contact relationship and position of impacted mandibular third molar teeth (IMM) with the mandibular canal (MC) in panoramic radiography (PR) images using deep learning (DL) models trained with the...

A novel way to use cross-validation to measure connectivity by machine learning allows epilepsy surgery outcome prediction.

NeuroImage
The rate of success of epilepsy surgery, ensuring seizure-freedom, is limited by the lack of epileptogenicity biomarkers. Previous evidence supports the critical role of functional connectivity during seizure generation to characterize the epileptoge...