AIMC Topic: Artificial Intelligence

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Potential Role of Machine Learning in Oncology.

The journal of contemporary dental practice
Machine learning (ML) is the ability of computers to learn from data autonomously. It is a core branch of artificial intelligence (AI), which is defined as the ability of a machine to replicate the intellectual processes of humans independently. The ...

Systems biology intertwines with single cell and AI.

BMC bioinformatics
A report of the 12th International Conference on Systems Biology (ISB2018), 18-21 August, Guiyang, China.

Sparse support vector machines with L approximation for ultra-high dimensional omics data.

Artificial intelligence in medicine
Omics data usually have ultra-high dimension (p) and small sample size (n). Standard support vector machines (SVMs), which minimize the L norm for the primal variables, only lead to sparse solutions for the dual variables. L based SVMs, directly mini...

Knowledge development, technology and questions of nursing ethics.

Nursing ethics
This article explores emerging ethical questions that result from knowledge development in a complex, technological age. Nursing practice is at a critical ideological and ethical precipice where decision-making is enhanced and burdened by new ways of...

Deep Learning/Artificial Intelligence and Blood-Based DNA Epigenomic Prediction of Cerebral Palsy.

International journal of molecular sciences
The etiology of cerebral palsy (CP) is complex and remains inadequately understood. Early detection of CP is an important clinical objective as this improves long term outcomes. We performed genome-wide DNA methylation analysis to identify epigenomic...

An Open Science Approach to Artificial Intelligence in Healthcare.

Yearbook of medical informatics
OBJECTIVES: Artificial Intelligence (AI) offers significant potential for improving healthcare. This paper discusses how an "open science" approach to AI tool development, data sharing, education, and research can support the clinical adoption of AI ...

Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications.

Yearbook of medical informatics
OBJECTIVES: This paper draws attention to: i) key considerations for evaluating artificial intelligence (AI) enabled clinical decision support; and ii) challenges and practical implications of AI design, development, selection, use, and ongoing surve...

Artificial Intelligence in Primary Health Care: Perceptions, Issues, and Challenges.

Yearbook of medical informatics
BACKGROUND: Artificial intelligence (AI) is heralded as an approach that might augment or substitute for the limited processing power of the human brain of primary health care (PHC) professionals. However, there are concerns that AI-mediated decision...

Role of Artificial Intelligence within the Telehealth Domain.

Yearbook of medical informatics
OBJECTIVES: This paper provides a discussion about the potential scope of applicability of Artificial Intelligence methods within the telehealth domain. These methods are focussed on clinical needs and provide some insight to current directions, base...