AIMC Topic: Neural Networks, Computer

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Automatic classification of medical image modality and anatomical location using convolutional neural network.

PloS one
Modern radiologic images comply with DICOM (digital imaging and communications in medicine) standard, which, upon conversion to other image format, would lose its image detail and information such as patient demographics or type of image modality tha...

Deep-learning based classification distinguishes sarcomatoid malignant mesotheliomas from benign spindle cell mesothelial proliferations.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Sarcomatoid mesothelioma is an aggressive malignancy that can be challenging to distinguish from benign spindle cell mesothelial proliferations based on biopsy, and this distinction is crucial to patient treatment and prognosis. A novel deep learning...

Wide range of applications for machine-learning prediction models in orthopedic surgical outcome: a systematic review.

Acta orthopaedica
Background and purpose - Advancements in software and hardware have enabled the rise of clinical prediction models based on machine learning (ML) in orthopedic surgery. Given their growing popularity and their likely implementation in clinical practi...

Artificial Intelligence in Endodontics: Current Applications and Future Directions.

Journal of endodontics
INTRODUCTION: Artificial intelligence (AI) has the potential to replicate human intelligence to perform prediction and complex decision making in health care and has significantly increased its presence and relevance in various tasks and applications...

MDC-net: A new convolutional neural network for nucleus segmentation in histopathology images with distance maps and contour information.

Computers in biology and medicine
Accurate segmentation of nuclei in digital pathology images can assist doctors in diagnosing diseases and evaluating subsequent treatments. Manual segmentation of nuclei from pathology images is time-consuming because of the large number of nuclei an...

Machine learning models for classification tasks related to drug safety.

Molecular diversity
In this review, we outline the current trends in the field of machine learning-driven classification studies related to ADME (absorption, distribution, metabolism and excretion) and toxicity endpoints from the past six years (2015-2021). The study fo...

Predictive online 3D target tracking with population-based generative networks for image-guided radiotherapy.

International journal of computer assisted radiology and surgery
PURPOSE: Respiratory motion of thoracic organs poses a severe challenge for the administration of image-guided radiotherapy treatments. Providing online and up-to-date volumetric information during free breathing can improve target tracking, ultimate...

Algebraic graph-assisted bidirectional transformers for molecular property prediction.

Nature communications
The ability of molecular property prediction is of great significance to drug discovery, human health, and environmental protection. Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Although s...