AIMC Topic: Female

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Machine Learning: The Next Paradigm Shift in Medical Education.

Academic medicine : journal of the Association of American Medical Colleges
Machine learning (ML) algorithms are powerful prediction tools with immense potential in the clinical setting. There are a number of existing clinical tools that use ML, and many more are in development. Physicians are important stakeholders in the h...

Predicting the Need For Vasopressors in the Intensive Care Unit Using an Attention Based Deep Learning Model.

Shock (Augusta, Ga.)
BACKGROUND: Previous models on prediction of shock mostly focused on septic shock and often required laboratory results in their models. The purpose of this study was to use deep learning approaches to predict vasopressor requirement for critically i...

Temporal Differential Expression of Physiomarkers Predicts Sepsis in Critically Ill Adults.

Shock (Augusta, Ga.)
BACKGROUND: Sepsis is a life-threatening condition with high mortality rates. Early detection and treatment are critical to improving outcomes. Our primary objective was to develop artificial intelligence capable of predicting sepsis earlier using a ...

Mortality risk stratification using artificial intelligence-augmented electrocardiogram in cardiac intensive care unit patients.

European heart journal. Acute cardiovascular care
AIMS: An artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm can identify left ventricular systolic dysfunction (LVSD). We sought to determine whether this AI-ECG algorithm could stratify mortality risk in cardiac intensive care un...

Robotic Applications for Benign Gynecologic Procedures.

Surgical technology international
INTRODUCTION: Robotic systems provide a platform for surgeons to expand their capabilities, allowing them to perform complex procedures safely and efficiently. Within the field of benign gynecology, this has become an increasingly popular option sinc...

Artificial Intelligence-Based Screening for Mycobacteria in Whole-Slide Images of Tissue Samples.

American journal of clinical pathology
OBJECTIVES: This study aimed to develop and validate a deep learning algorithm to screen digitized acid fast-stained (AFS) slides for mycobacteria within tissue sections.

Machine Learning Algorithms Predict Functional Improvement After Hip Arthroscopy for Femoroacetabular Impingement Syndrome in Athletes.

The Journal of bone and joint surgery. American volume
BACKGROUND: Despite previous reports of improvements for athletes following hip arthroscopy for femoroacetabular impingement syndrome (FAIS), many do not achieve clinically relevant outcomes. The purpose of this study was to develop machine learning ...

Machine Learning-based Prediction Model for Treatment of Acromegaly With First-generation Somatostatin Receptor Ligands.

The Journal of clinical endocrinology and metabolism
CONTEXT: Artificial intelligence (AI), in particular machine learning (ML), may be used to deeply analyze biomarkers of response to first-generation somatostatin receptor ligands (fg-SRLs) in the treatment of acromegaly.

Clinically applicable artificial intelligence algorithm for the diagnosis, evaluation, and monitoring of acute retinal necrosis.

Journal of Zhejiang University. Science. B
The prompt detection and proper evaluation of necrotic retinal region are especially important for the diagnosis and treatment of acute retinal necrosis (ARN). The potential application of artificial intelligence (AI) algorithms in these areas of cli...

Predicting Spinal Surgery Candidacy From Imaging Data Using Machine Learning.

Neurosurgery
BACKGROUND: The referral process for consultation with a spine surgeon remains inefficient, given a substantial proportion of referrals to spine surgeons are nonoperative.