AIMC Topic: Databases, Factual

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Deep multi-task learning for nephropathy diagnosis on immunofluorescence images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: As an advanced technique, immunofluorescence (IF) is one of the most widely-used medical image for nephropathy diagnosis, due to its ease of acquisition with low cost. In practice, the clinically collected IF images are comm...

Application and evaluation of surgical tool and tool tip recognition based on Convolutional Neural Network in multiple endoscopic surgical scenarios.

Surgical endoscopy
BACKGROUND: In recent years, computer-assisted intervention and robot-assisted surgery are receiving increasing attention. The need for real-time identification and tracking of surgical tools and tool tips is constantly demanding. A series of researc...

Generative adversarial networks in electrocardiogram synthesis: Recent developments and challenges.

Artificial intelligence in medicine
Training deep neural network classifiers for electrocardiograms (ECGs) requires sufficient data. However, imbalanced datasets pose a major problem for the training process and hence data augmentation is commonly performed. Generative adversarial netw...

Deep neural network pulmonary nodule segmentation methods for CT images: Literature review and experimental comparisons.

Computers in biology and medicine
Automatic and accurate segmentation of pulmonary nodules in CT images can help physicians perform more accurate quantitative analysis, diagnose diseases, and improve patient survival. In recent years, with the development of deep learning technology,...

Improving the classification of cardinality phenotypes using collections.

Journal of biomedical semantics
MOTIVATION: Phenotypes are observable characteristics of an organism and they can be highly variable. Information about phenotypes is collected in a clinical context to characterize disease, and is also collected in model organisms and stored in mode...

Fragments quantum descriptors in classification of bio-accumulative compounds.

Journal of molecular graphics & modelling
The aim of the following research is to assess the applicability of calculated quantum properties of molecular fragments as molecular descriptors in machine learning classification task. The research is based on bio-concentration and QM9-extended dat...

Spatial attention-based residual network for human burn identification and classification.

Scientific reports
Diagnosing burns in humans has become critical, as early identification can save lives. The manual process of burn diagnosis is time-consuming and complex, even for experienced doctors. Machine learning (ML) and deep convolutional neural network (CNN...

The ROCEEH Out of Africa Database (ROAD): A large-scale research database serves as an indispensable tool for human evolutionary studies.

PloS one
Large scale databases are critical for helping scientists decipher long-term patterns in human evolution. This paper describes the conception and development of such a research database and illustrates how big data can be harnessed to formulate new i...

Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Machine learning on electromyography (EMG) has recently achieved remarkable success on various tasks, while such success relies heavily on the assumption that the training and future data must be of the same data distribution. However, this assumptio...

Application of Artificial intelligence in COVID-19-related geriatric care: A scoping review.

Archives of gerontology and geriatrics
BACKGROUND: Older adults have been disproportionately affected by the COVID-19 pandemic. This scoping review aimed to summarize the current evidence of artificial intelligence (AI) use in the screening/monitoring, diagnosis, and/or treatment of COVID...