AIMC Topic: Humans

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Prediction of proliferative diabetic retinopathy using machine learning in Latino and non-Hispanic black cohorts with routine blood and urine testing.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
PURPOSE: The objective was to predict proliferative diabetic retinopathy (PDR) in non-Hispanic Black (NHB) and Latino (LA) patients by applying machine learning algorithms to routinely collected blood and urine laboratory results.

Oral mucosal lesions triage via YOLOv7 models.

Journal of the Formosan Medical Association = Taiwan yi zhi
BACKGROUND/PURPOSE: The global incidence of lip and oral cavity cancer continues to rise, necessitating improved early detection methods. This study leverages the capabilities of computer vision and deep learning to enhance the early detection and cl...

Assessing ChatGPT's theoretical knowledge and prescriptive accuracy in bacterial infections: a comparative study with infectious diseases residents and specialists.

Infection
OBJECTIVES: Advancements in Artificial Intelligence(AI) have made platforms like ChatGPT increasingly relevant in medicine. This study assesses ChatGPT's utility in addressing bacterial infection-related questions and antibiogram-based clinical cases...

Redefining a new frontier in alkaptonuria therapy with AI-driven drug candidate design via innovation.

Zeitschrift fur Naturforschung. C, Journal of biosciences
A rare metabolic condition called alkaptonuria (AKU) is caused by a decrease in homogentisate 1,2 dioxygenase (HGO) activity due to a mutation in homogentisate dioxygenase (HGD) gene. Homogentisic acid is a byproduct of the catabolism of tyrosine and...

The value of deep learning-based X-ray techniques in detecting and classifying K-L grades of knee osteoarthritis: a systematic review and meta-analysis.

European radiology
OBJECTIVES: Knee osteoarthritis (KOA), a prevalent degenerative joint disease, is primarily diagnosed through X-ray imaging. The Kellgren-Lawrence grading system (K-L) is the gold standard for evaluating KOA severity through X-ray analysis. However, ...

Deep learning methods for protein function prediction.

Proteomics
Predicting protein function from protein sequence, structure, interaction, and other relevant information is important for generating hypotheses for biological experiments and studying biological systems, and therefore has been a major challenge in p...

Large-Scale Study on AI's Impact on Identifying Chest Radiographs with No Actionable Disease in Outpatient Imaging.

Academic radiology
RATIONALE AND OBJECTIVES: Given the high volume of chest radiographs, radiologists frequently encounter heavy workloads. In outpatient imaging, a substantial portion of chest radiographs show no actionable findings. Automatically identifying these ca...

A Novel Deep Learning-based Artificial Intelligence System for Interpreting Urolithiasis in Computed Tomography.

European urology focus
BACKGROUND AND OBJECTIVE: Our aim was to develop an artificial intelligence (AI) system for detection of urolithiasis in computed tomography (CT) images using advanced deep learning capable of real-time calculation of stone parameters such as volume ...

Predictors of left atrial appendage thrombus in atrial fibrillation patients undergoing cardioversion.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing
BACKGROUND: Atrial fibrillation and atrial flutter represent the most prevalent clinically significant cardiac arrhythmias. While the CHA2DS2-VASc score is commonly used to inform anticoagulation therapy decisions for patients with these conditions, ...

Screening for diabetic retinopathy with artificial intelligence: a real world evaluation.

Acta diabetologica
AIM: Periodic screening for diabetic retinopathy (DR) is effective for preventing blindness. Artificial intelligence (AI) systems could be useful for increasing the screening of DR in diabetic patients. The aim of this study was to compare the perfor...