AIMC Topic: Deep Learning

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You get the best of both worlds? Integrating deep learning and traditional machine learning for breast cancer risk prediction.

Computers in biology and medicine
Breast Cancer is the most commonly diagnosed cancer worldwide. While screening mammography diminishes the burden of this disease, it has some flaws related to the presence of false negatives. Adapting screening to each woman's needs could help overco...

Deep Learning-Enhanced Chemiluminescence Vertical Flow Assay for High-Sensitivity Cardiac Troponin I Testing.

Small (Weinheim an der Bergstrasse, Germany)
Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible format. Here, high-sensitivity detection of cardiac troponin I (cTnI) is demonstrated through innovations...

Fuzz Testing Molecular Representation Using Deep Variational Anomaly Generation.

Journal of chemical information and modeling
Researchers are developing increasingly robust molecular representations, motivating the need for thorough methods to stress-test and validate them. Here, we use a variational auto-encoder (VAE), an unsupervised deep learning model, to generate anoma...

Deep learning radiomics nomogram for preoperatively identifying moderate-to-severe chronic cholangitis in children with pancreaticobiliary maljunction: a multicenter study.

BMC medical imaging
BACKGROUND: Long-term severe cholangitis can lead to dense adhesions and increased fragility of the bile duct, complicating surgical procedures and elevating operative risk in children with pancreaticobiliary maljunction (PBM). Consequently, preopera...

Artificial intelligence-driven ensemble deep learning models for smart monitoring of indoor activities in IoT environment for people with disabilities.

Scientific reports
Disabled persons demanding healthcare is a developing global occurrence. The support in longer-term care includes nursing, intricate medical, recovery, and social help services. The price is large, but advanced technologies can aid in decreasing expe...

Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection.

Scientific reports
Employing two standard mammography views is crucial for radiologists, providing comprehensive insights for reliable clinical evaluations. This study introduces paired mammogram view based-network(PMVnet), a novel algorithm designed to enhance breast ...

Breast cancer classification based on hybrid CNN with LSTM model.

Scientific reports
Breast cancer (BC) is a global problem, largely due to a shortage of knowledge and early detection. The speed-up process of detection and classification is crucial for effective cancer treatment. Medical image analysis methods and computer-aided diag...

Detection of Alzheimer Disease in Neuroimages Using Vision Transformers: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Alzheimer disease (AD) is a progressive condition characterized by cognitive decline and memory loss. Vision transformers (ViTs) are emerging as promising deep learning models in medical imaging, with potential applications in the detecti...

Syn2Real: synthesis of CT image ring artifacts for deep learning-based correction.

Physics in medicine and biology
. We strive to overcome the challenges posed by ring artifacts in x-ray computed tomography (CT) by developing a novel approach for generating training data for deep learning-based methods. Training such networks require large, high quality, datasets...

Artificial Intelligence in Pediatric Endocrinology.

Advances in pediatrics
The rapid technological progress over the last couple of decades has paved the way for innovative methods capable of solving scientific questions at a rate far exceeding human capabilities. One prime example is the field of artificial intelligence (A...