AIMC Topic: Deep Learning

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Prediction of lymphoma response to CAR T cells by deep learning-based image analysis.

PloS one
Clinical prognostic scoring systems have limited utility for predicting treatment outcomes in lymphomas. We therefore tested the feasibility of a deep-learning (DL)-based image analysis methodology on pre-treatment diagnostic computed tomography (dCT...

Attention-based deep learning framework to recognize diabetes disease from cellular retinal images.

Biochemistry and cell biology = Biochimie et biologie cellulaire
A medical disorder known as diabetic retinopathy (DR) affects people who suffer from diabetes. Many people are visually impaired due to DR. Primary cause of DR in patients is high blood sugar, and it affects blood vessels available in the retinal cel...

Harnessing the power of AI: Advanced deep learning models optimization for accurate SARS-CoV-2 forecasting.

PloS one
The pandemic has significantly affected many countries including the USA, UK, Asia, the Middle East and Africa region, and many other countries. Similarly, it has substantially affected Malaysia, making it crucial to develop efficient and precise for...

Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis.

PloS one
Facial expressions are widely recognized as universal indicators of underlying internal states in most species of animals, thereby presenting as a non-invasive measure for assessing physical and mental conditions. Despite the advancement of artificia...

Deep learning-based local SAR prediction using B maps and structural MRI of the head for parallel transmission at 7 T.

Magnetic resonance in medicine
PURPOSE: To predict subject-specific local specific absorption rate (SAR) distributions of the human head for parallel transmission (pTx) systems at 7 T.

Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data.

AJR. American journal of roentgenology
The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon m...

Multimodal Deep Learning Classifier for Primary Open Angle Glaucoma Diagnosis Using Wide-Field Optic Nerve Head Cube Scans in Eyes With and Without High Myopia.

Journal of glaucoma
PRCIS: An optical coherence tomography (OCT)-based multimodal deep learning (DL) classification model, including texture information, is introduced that outperforms single-modal models and multimodal models without texture information for glaucoma di...

Improvement of phoswich detector-based β+/γ-ray discrimination algorithm with deep learning.

Medical physics
BACKGROUND: Positron probes can accurately localize malignant tumors by directly detecting positrons emitted from positron-emitting radiopharmaceuticals that accumulate in malignant tumors. In the conventional method for direct positron detection, mu...

Imaging inside highly scattering media using hybrid deep learning and analytical algorithm.

Journal of biophotonics
Imaging through highly scattering media is a challenging problem with numerous applications in biomedical and remote-sensing fields. Existing methods that use analytical or deep learning tools are limited by simplified forward models or a requirement...