AIMC Topic: Deep Learning

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Artificial Intelligence in Nuclear Cardiology.

Heart failure clinics
Artificial intelligence (AI) encompasses a variety of computer algorithms that have a wide range of potential clinical applications in nuclear cardiology. This article will introduce core terminology and concepts for AI including classifications of A...

Optimization enabled ensemble based deep learning model for elderly falling risk prediction.

Computer methods in biomechanics and biomedical engineering
Predicting fall risk in the elderly is crucial for enhancing safety and well-being. Aging and chronic diseases often impair balance, increasing fall risk. This study aims to develop an advanced fall risk prediction model using an optimized deep learn...

U-Attention-Net: a deep learning automatic delineation model for parotid glands in head and neck cancer organs at risk on radiotherapy localization computed tomography images.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
OBJECTIVE: This study aimed to develop a novel deep learning model, U-Attention-Net (UA-Net), for precise segmentation of parotid glands on radiotherapy localization CT images.

Deep Learning Reveals Liver MRI Features Associated With PNPLA3 I148M in Steatotic Liver Disease.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND: Steatotic liver disease (SLD) is the most common liver disease worldwide, affecting 30% of the global population. It is strongly associated with the interplay of genetic and lifestyle-related risk factors. The genetic variant accounting f...

Time-series deep learning and conformal prediction for improved sepsis diagnosis in primarily Non-ICU hospitalized patients.

Computers in biology and medicine
PURPOSE: Sepsis, a life-threatening condition from an uncontrolled immune response to infection, is a leading cause of in-hospital mortality. Early detection is crucial, yet traditional diagnostic methods, like SIRS and SOFA, often fail to identify s...

Multiclass ensemble framework for enhanced prostate gland Segmentation: Integrating Self-ONN decoders with EfficientNet.

Computers in biology and medicine
Digital pathology relies on the morphological architecture of prostate glands to recognize cancerous tissue. Prostate cancer (PCa) originates in walnut shaped prostate gland in the male reproductive system. Deep learning (DL) pipelines can assist in ...

A medical information extraction model with contrastive tuning and tagging layer training.

Computers in biology and medicine
Medical information extraction, as a core task in medical intelligent systems, focuses on extracting necessary structured information from clinical texts. In recent years, deep learning-based methods have become mainstream and often achieve superior ...

Automatic adult age estimation using bone mineral density of proximal femur via deep learning.

Forensic science international
Accurate adult age estimation (AAE) is critical for forensic and anthropological applications, yet traditional methods relying on bone mineral density (BMD) face significant challenges due to biological variability and methodological limitations. Thi...

Estimation of time-to-total knee replacement surgery with multimodal modeling and artificial intelligence.

Computers in biology and medicine
BACKGROUND: The methods for predicting time-to-total knee replacement (TKR) do not provide enough information to make robust and accurate predictions.

Machine learning in neuroimaging and computational pathophysiology of Parkinson's disease: A comprehensive review and meta-analysis.

Asian journal of psychiatry
In recent years, machine learning and deep learning have shown potential for improving Parkinson's disease (PD) diagnosis, one of the most common neurodegenerative diseases. This comprehensive analysis examines machine learning and deep learning-base...