AIMC Topic: Deep Learning

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Multi-objective optimization determines when, which and how to fuse deep networks: An application to predict COVID-19 outcomes.

Computers in biology and medicine
The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific community, after being involved with detecting COVID-19 signs in medical images, has been now directing the efforts towards the development of methods that ca...

Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients.

Computers in biology and medicine
Tumor burden assessment by magnetic resonance imaging (MRI) is central to the evaluation of treatment response for glioblastoma. This assessment is, however, complex to perform and associated with high variability due to the high heterogeneity and co...

Dual parallel net: A novel deep learning model for rectal tumor segmentation via CNN and transformer with Gaussian Mixture prior.

Journal of biomedical informatics
Segmentation of rectal cancerous regions from Magnetic Resonance (MR) images can help doctor define the extent of the rectal cancer and judge the severity of rectal cancer, so rectal tumor segmentation is crucial to improve the accuracy of rectal can...

Models and data of AMPlify: a deep learning tool for antimicrobial peptide prediction.

BMC research notes
OBJECTIVES: Antibiotic resistance is a rising global threat to human health and is prompting researchers to seek effective alternatives to conventional antibiotics, which include antimicrobial peptides (AMPs). Recently, we have reported AMPlify, an a...

Biologically informed deep learning to query gene programs in single-cell atlases.

Nature cell biology
The increasing availability of large-scale single-cell atlases has enabled the detailed description of cell states. In parallel, advances in deep learning allow rapid analysis of newly generated query datasets by mapping them into reference atlases. ...

Simulation of Postoperative Facial Appearances via Geometric Deep Learning for Efficient Orthognathic Surgical Planning.

IEEE transactions on medical imaging
Orthognathic surgery corrects jaw deformities to improve aesthetics and functions. Due to the complexity of the craniomaxillofacial (CMF) anatomy, orthognathic surgery requires precise surgical planning, which involves predicting postoperative change...

Simultaneous Segmentation and Classification of Pressure Injury Image Data Using Mask-R-CNN.

Computational and mathematical methods in medicine
BACKGROUND: Pressure injuries (PIs) impose a substantial burden on patients, caregivers, and healthcare systems, affecting an estimated 3 million Americans and costing nearly $18 billion annually. Accurate pressure injury staging remains clinically c...

Deep Learning and Medical Image Processing Techniques for Diabetic Retinopathy: A Survey of Applications, Challenges, and Future Trends.

Journal of healthcare engineering
Diabetic retinopathy (DR) is a common eye retinal disease that is widely spread all over the world. It leads to the complete loss of vision based on the level of severity. It damages both retinal blood vessels and the eye's microscopic interior layer...

Deep learning-based diagnosis of feline hypertrophic cardiomyopathy.

PloS one
Feline hypertrophic cardiomyopathy (HCM) is a common heart disease affecting 10-15% of all cats. Cats with HCM exhibit breathing difficulties, lethargy, and heart murmur; furthermore, feline HCM can also result in sudden death. Among various methods ...