AIMC Topic: Artificial Intelligence

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Strengths and Opportunities of Network Medicine in Cardiovascular Diseases.

Circulation journal : official journal of the Japanese Circulation Society
Network medicine can advance current medical practice by arising as response to the limitations of a reductionist approach focusing on cardiovascular (CV) diseases as a direct consequence of a single defect. This molecular-bioinformatic approach inte...

Artificial intelligence in digital breast pathology: Techniques and applications.

Breast (Edinburgh, Scotland)
Breast cancer is the most common cancer and second leading cause of cancer-related death worldwide. The mainstay of breast cancer workup is histopathological diagnosis - which guides therapy and prognosis. However, emerging knowledge about the comple...

EEG-based image classification via a region-level stacked bi-directional deep learning framework.

BMC medical informatics and decision making
BACKGROUND: As a physiological signal, EEG data cannot be subjectively changed or hidden. Compared with other physiological signals, EEG signals are directly related to human cortical activities with excellent temporal resolution. After the rapid dev...

Ethical concerns with the use of intelligent assistive technology: findings from a qualitative study with professional stakeholders.

BMC medical ethics
BACKGROUND: Advances in artificial intelligence (AI), robotics and wearable computing are creating novel technological opportunities for mitigating the global burden of population ageing and improving the quality of care for older adults with dementi...

Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study.

Computational and mathematical methods in medicine
Machine learning, one of the core disciplines of artificial intelligence, is an approach whose main emphasis is analytical model building. In other words, machine learning enables an automaton to make its own decisions based on a previous training pr...

Implementation of artificial intelligence in medicine: Status analysis and development suggestions.

Artificial intelligence in medicine
The general public's attitudes, demands, and expectations regarding medical AI could provide guidance for the future development of medical AI to satisfy the increasing needs of doctors and patients. The objective of this study is to investigate publ...

Validation Study of QSAR/DNN Models Using the Competition Datasets.

Molecular informatics
Since the QSAR/DNN model showed predominant predictive performance over other conventional methods in the Kaggle QSAR competition, many artificial neural network (ANN) methods have been applied to drug and material discovery. Appearance of artificial...