AIMC Topic: Deep Learning

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Deep Spatio-Temporal Network for Low-SNR Cryo-EM Movie Frame Enhancement.

IEEE/ACM transactions on computational biology and bioinformatics
Cryo-EM in single particle analysis is known to have low SNR and requires to utilize several frames of the same particle sample to restore one high-quality image for visualizing that particle. However, the low SNR of cryo-EM movie and motion caused b...

TDFFM: Transformer and Deep Forest Fusion Model for Predicting Coronavirus 3C-Like Protease Cleavage Sites.

IEEE/ACM transactions on computational biology and bioinformatics
COVID-19, caused by the highly contagious SARS-CoV-2 virus, is distinguished by its positive-sense, single-stranded RNA genome. A thorough understanding of SARS-CoV-2 pathogenesis is crucial for halting its proliferation. Notably, the 3C-like proteas...

Improving Clinical Decision Making With a Two-Stage Recommender System.

IEEE/ACM transactions on computational biology and bioinformatics
Clinical decision-making is complex and time-intensive. To help in this effort, clinical recommender systems (RS) have been designed to facilitate healthcare practitioners with personalized advice. However, designing an effective clinical RS poses ch...

Evaluation of the accuracy of automated segmentation based on deep learning for prostate cancer patients.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists
PURPOSE: This study evaluated the accuracy of a commercial deep learning (DL)-based algorithm for segmenting the prostate, seminal vesicles (SV), and organs at risk (OAR) in patients with prostate cancer.

DeepCOVIDNet-CXR: deep learning strategies for identifying COVID-19 on enhanced chest X-rays.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: COVID-19 is one of the recent major epidemics, which accelerates its mortality and prevalence worldwide. Most literature on chest X-ray-based COVID-19 analysis has focused on multi-case classification (COVID-19, pneumonia, and normal) by ...

Trap colour strongly affects the ability of deep learning models to recognize insect species in images of sticky traps.

Pest management science
BACKGROUND: The use of computer vision and deep learning models to automatically classify insect species on sticky traps has proven to be a cost- and time-efficient approach to pest monitoring. As different species are attracted to different colours,...

Rapid detection of mouse spermatogenic defects by testicular cellular composition analysis via enhanced deep learning model.

Andrology
BACKGROUND: Histological analysis of the testicular sections is paramount in infertility research but tedious and often requires months of training and practice.

Deep Conformal Supervision: Leveraging Intermediate Features for Robust Uncertainty Quantification.

Journal of imaging informatics in medicine
Trustworthiness is crucial for artificial intelligence (AI) models in clinical settings, and a fundamental aspect of trustworthy AI is uncertainty quantification (UQ). Conformal prediction as a robust uncertainty quantification (UQ) framework has bee...

Enhancing dental caries classification in CBCT images by using image processing and self-supervised learning.

Computers in biology and medicine
Diagnosing dental caries poses a significant challenge in dentistry, necessitating precise and early detection for effective management. This study utilizes Self-Supervised Learning (SSL) tasks to improve the classification of dental caries in Cone B...