AIMC Topic: Deep Learning

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Variant Effect Prediction in the Age of Machine Learning.

Cold Spring Harbor perspectives in biology
Over the years, many computational methods have been created for the analysis of the impact of single amino acid substitutions resulting from single-nucleotide variants in genome coding regions. Historically, all methods have been supervised and thus...

Mixed Supervision of Histopathology Improves Prostate Cancer Classification From MRI.

IEEE transactions on medical imaging
Non-invasive prostate cancer classification from MRI has the potential to revolutionize patient care by providing early detection of clinically significant disease, but has thus far shown limited positive predictive value. To address this, we present...

Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers With Partially Annotated Ultrasound Images.

IEEE transactions on medical imaging
Deep learning (DL) has proven highly effective for ultrasound-based computer-aided diagnosis (CAD) of breast cancers. In an automatic CAD system, lesion detection is critical for the following diagnosis. However, existing DL-based methods generally r...

A CNN-CBAM-BIGRU model for protein function prediction.

Statistical applications in genetics and molecular biology
Understanding a protein's function based solely on its amino acid sequence is a crucial but intricate task in bioinformatics. Traditionally, this challenge has proven difficult. However, recent years have witnessed the rise of deep learning as a powe...

Assessing the risk of takeover catastrophe from large language models.

Risk analysis : an official publication of the Society for Risk Analysis
This article presents a risk analysis of large language models (LLMs), a type of "generative" artificial intelligence (AI) system that produces text, commonly in response to textual inputs from human users. The article is specifically focused on the ...

A Comparison of CT-Based Pancreatic Segmentation Deep Learning Models.

Academic radiology
RATIONALE AND OBJECTIVES: Pancreas segmentation accuracy at CT is critical for the identification of pancreatic pathologies and is essential for the development of imaging biomarkers. Our objective was to benchmark the performance of five high-perfor...

A geometric approach to robust medical image segmentation.

Medical image analysis
Robustness of deep learning segmentation models is crucial for their safe incorporation into clinical practice. However, these models can falter when faced with distributional changes. This challenge is evident in magnetic resonance imaging (MRI) sca...

VmmScore: An umami peptide prediction and receptor matching program based on a deep learning approach.

Computers in biology and medicine
Peptides, with recognized physiological and medical implications, such as the ability to lower blood pressure and lipid levels, are central to our research on umami taste perception. This study introduces a computational strategy to tackle the challe...

MSE-VGG: A Novel Deep Learning Approach Based on EEG for Rapid Ischemic Stroke Detection.

Sensors (Basel, Switzerland)
Ischemic stroke is a type of brain dysfunction caused by pathological changes in the blood vessels of the brain which leads to brain tissue ischemia and hypoxia and ultimately results in cell necrosis. Without timely and effective treatment in the ea...

Evaluation of deep learning algorithms in detecting moyamoya disease: a systematic review and single-arm meta-analysis.

Neurosurgical review
The diagnosis of Moyamoya disease (MMD) relies heavily on imaging, which could benefit from standardized machine learning tools. This study aims to evaluate the diagnostic efficacy of deep learning (DL) algorithms for MMD by analyzing sensitivity, sp...