AIMC Topic: Algorithms

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The potential applications of artificial intelligence in drug discovery and development.

Physiological research
Development of a new dug is a very lengthy and highly expensive process since only preclinical, pharmacokinetic, pharmacodynamic and toxicological studies include a multiple of in silico, in vitro, in vivo experimentations that traditionally last sev...

[Application of Artificial Intelligence in Clinical Genomics].

Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae
Clinical genomics mainly studies the clinical application of genomics in diagnosis,treatment decision,and prognosis prediction.Artificial intelligence enables the processing of complex and massive data in genomics which are difficult to be dealt with...

Trust in AI: why we should be designing for APPROPRIATE reliance.

Journal of the American Medical Informatics Association : JAMIA
Use of artificial intelligence in healthcare, such as machine learning-based predictive algorithms, holds promise for advancing outcomes, but few systems are used in routine clinical practice. Trust has been cited as an important challenge to meaning...

[Research status and prospect of artificial intelligence technology in the diagnosis of urinary system tumors].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
With the rapid development of artificial intelligence technology, researchers have applied it to the diagnosis of various tumors in the urinary system in recent years, and have obtained many valuable research results. The article sorted the research ...

Artificial intelligence in the diagnosis and detection of heart failure: the past, present, and future.

Reviews in cardiovascular medicine
Artificial Intelligence (AI) performs human intelligence-dependant tasks using tools such as Machine Learning, and its subtype Deep Learning. AI has incorporated itself in the field of cardiovascular medicine, and increasingly employed to revolutioni...

AI-based forecasting of ethanol fermentation using yeast morphological data.

Bioscience, biotechnology, and biochemistry
Several industries require getting information of products as soon as possible during fermentation. However, the trade-off between sensing speed and data quantity presents challenges for forecasting fermentation product yields. In this study, we trie...

[Analysis of the performance of a multi-view fusion and active contour constraint based deep learning algorithm for ossicles segmentation on 10 μm otology CT].

Zhonghua yi xue za zhi
To explore the performance of a deep learning algorithm that combined multi-view fusion with active contour constrained for ossicles segmentation on the 10 μm otology CT images. The 10 μm otology CT image data from 79 cases (56 cases were from volu...

CoCoNet-boosting RNA contact prediction by convolutional neural networks.

Nucleic acids research
Co-evolutionary models such as direct coupling analysis (DCA) in combination with machine learning (ML) techniques based on deep neural networks are able to predict accurate protein contact or distance maps. Such information can be used as constraint...

Deep learning multi-shot 3D localization microscopy using hybrid optical-electronic computing.

Optics letters
Current 3D localization microscopy approaches are fundamentally limited in their ability to image thick, densely labeled specimens. Here, we introduce a hybrid optical-electronic computing approach that jointly optimizes an optical encoder (a set of ...

Confidence-Controlled Hebbian Learning Efficiently Extracts Category Membership From Stimuli Encoded in View of a Categorization Task.

Neural computation
In experiments on perceptual decision making, individuals learn a categorization task through trial-and-error protocols. We explore the capacity of a decision-making attractor network to learn a categorization task through reward-based, Hebbian-type ...