AIMC Topic: Deep Learning

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Explainable AI-driven scalogram analysis and optimized transfer learning for sleep apnea detection with single-lead electrocardiograms.

Computers in biology and medicine
Sleep apnea, a fatal sleep disorder causing repetitive respiratory cessation, requires immediate intervention due to neuropsychological issues. However, existing approaches such as polysomnography, considered the most reliable and accurate test to de...

Point-annotation supervision for robust 3D pulmonary infection segmentation by CT-based cascading deep learning.

Computers in biology and medicine
Infected region segmentation is crucial for pulmonary infection diagnosis, severity assessment, and monitoring treatment progression. High-performance segmentation methods rely heavily on fully annotated, large-scale training datasets. However, manua...

A Novel Deep Learning-Based (3D U-Net Model) Automated Pulmonary Nodule Detection Tool for CT Imaging.

Current oncology (Toronto, Ont.)
BACKGROUND: Precise detection and characterization of pulmonary nodules on computed tomography (CT) is crucial for early diagnosis and management.

Exploration of the optimal deep learning model for english-Japanese machine translation of medical device adverse event terminology.

BMC medical informatics and decision making
BACKGROUND: In Japan, reporting of medical device malfunctions and related health problems is mandatory, and efforts are being made to standardize terminology through the Adverse Event Terminology Collection of the Japan Federation of Medical Device ...

Severe deviation in protein fold prediction by advanced AI: a case study.

Scientific reports
Artificial intelligence (AI) and deep learning are making groundbreaking strides in protein structure prediction. AlphaFold is remarkable in this arena for its outstanding accuracy in modelling proteins fold based solely on their amino acid sequences...

Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images.

Scientific reports
Cancer is a global health concern because of a significant mortality rate and a wide range of affected organs. Early detection and accurate classification of cancer types are crucial for effective treatment. Imaging tests on different image modalitie...

Deep Learning Reconstruction Combined With Conventional Acceleration Improves Image Quality of 3 T Brain MRI and Does Not Impact Quantitative Diffusion Metrics.

Investigative radiology
OBJECTIVES: Deep learning reconstruction of magnetic resonance imaging (MRI) allows to either improve image quality of accelerated sequences or to generate high-resolution data. We evaluated the interaction of conventional acceleration and Deep Resol...

A novel deep learning framework for retinal disease detection leveraging contextual and local features cues from retinal images.

Medical & biological engineering & computing
Retinal diseases are a serious global threat to human vision, and early identification is essential for effective prevention and treatment. However, current diagnostic methods rely on manual analysis of fundus images, which heavily depends on the exp...

Evaluation of deep learning-based scatter correction on a long-axial field-of-view PET scanner.

European journal of nuclear medicine and molecular imaging
OBJECTIVE: Long-axial field-of-view (LAFOV) positron emission tomography (PET) systems allow higher sensitivity, with an increased number of detected lines of response induced by a larger angle of acceptance. However this extended angle increases the...

Robust deep learning from weakly dependent data.

Neural networks : the official journal of the International Neural Network Society
Recent developments on deep learning established some theoretical properties of deep neural networks estimators. However, most of the existing works on this topic are restricted to bounded loss functions or (sub)-Gaussian or bounded variables. This p...