AIMC Topic: Deep Learning

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Magicmol: a light-weighted pipeline for drug-like molecule evolution and quick chemical space exploration.

BMC bioinformatics
The flourishment of machine learning and deep learning methods has boosted the development of cheminformatics, especially regarding the application of drug discovery and new material exploration. Lower time and space expenses make it possible for sci...

A deep learning-based approach for statistical robustness evaluation in proton therapy treatment planning: a feasibility study.

Physics in medicine and biology
. Robustness evaluation is critical in particle radiotherapy due to its susceptibility to uncertainties. However, the customary method for robustness evaluation only considers a few uncertainty scenarios, which are insufficient to provide a consisten...

Deep learning enables MV-based real-time image guided radiation therapy for prostate cancer patients.

Physics in medicine and biology
. Using MV images for real-time image guided radiation therapy (IGRT) is ideal as it does not require additional imaging equipment, adds no additional imaging dose and provides motion data in the treatment beam frame of reference. However, accurate t...

Experimental validation of computer-vision methods for the successful detection of endodontic treatment obturation and progression from noisy radiographs.

Oral radiology
PURPOSE: (1) To evaluate the effects of denoising and data balancing on deep learning to detect endodontic treatment outcomes from radiographs. (2) To develop and train a deep-learning model and classifier to predict obturation quality from radiomics...

Portable deep-learning decoder for motor imaginary EEG signals based on a novel compact convolutional neural network incorporating spatial-attention mechanism.

Medical & biological engineering & computing
Due to high computational requirements, deep-learning decoders for motor imaginary (MI) electroencephalography (EEG) signals are usually implemented on bulky and heavy computing devices that are inconvenient for physical actions. To date, the applica...

Application of machine learning and deep learning methods for hydrated electron rate constant prediction.

Environmental research
Accurately determining the second-order rate constant with e (k) for organic compounds (OCs) is crucial in the e induced advanced reduction processes (ARPs). In this study, we collected 867 k values at different pHs from peer-reviewed publications an...

MutBLESS: A tool to identify disease-prone sites in cancer using deep learning.

Biochimica et biophysica acta. Molecular basis of disease
Understanding the molecular basis and impact of mutations at different stages of cancer are long-standing challenges in cancer biology. Identification of driver mutations from experiments is expensive and time intensive. In the present study, we coll...

Contribution of whole slide imaging-based deep learning in the assessment of intraoperative and postoperative sections in neuropathology.

Brain pathology (Zurich, Switzerland)
The pathological diagnosis of intracranial germinoma (IG), oligodendroglioma, and low-grade astrocytoma on intraoperative frozen section (IFS) and hematoxylin-eosin (HE)-staining section directly determines patients' treatment options, but it is a di...

Adrenal lesion classification with abdomen caps and the effect of ROI size.

Physical and engineering sciences in medicine
Accurate classification of adrenal lesions on magnetic resonance (MR) images are very important for diagnosis and treatment planning. The detection and classification of lesions in medical imaging heavily rely on several key factors, including the sp...

LAVA HyperSense and deep-learning reconstruction for near-isotropic (3D) enhanced magnetic resonance enterography in patients with Crohn's disease: utility in noise reduction and image quality improvement.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: This study aimed to compare near-isotropic contrast-enhanced T1-weighted (CE-T1W) magnetic resonance enterography (MRE) images reconstructed with vendor-supplied deep-learning reconstruction (DLR) with those reconstructed conventionally in t...