AI Medical Compendium Topic

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Biomedical Research

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Learning on knowledge graph dynamics provides an early warning of impactful research.

Nature biotechnology
The scientific ecosystem relies on citation-based metrics that provide only imperfect, inconsistent and easily manipulated measures of research quality. Here we describe DELPHI (Dynamic Early-warning by Learning to Predict High Impact), a framework t...

Presenting artificial intelligence, deep learning, and machine learning studies to clinicians and healthcare stakeholders: an introductory reference with a guideline and a Clinical AI Research (CAIR) checklist proposal.

Acta orthopaedica
Background and purpose - Artificial intelligence (AI), deep learning (DL), and machine learning (ML) have become common research fields in orthopedics and medicine in general. Engineers perform much of the work. While they gear the results towards he...

Automated biomarker candidate discovery in imaging mass spectrometry data through spatially localized Shapley additive explanations.

Analytica chimica acta
The search for molecular species that are differentially expressed between biological states is an important step towards discovering promising biomarker candidates. In imaging mass spectrometry (IMS), performing this search manually is often impract...

A primer on applying AI synergistically with domain expertise to oncology.

Biochimica et biophysica acta. Reviews on cancer
BACKGROUND: The concurrent growth of large-scale oncology data alongside the computational methods with which to analyze and model it has created a promising environment for revolutionizing cancer diagnosis, treatment, prevention, and drug discovery....

COVID-19 in the Age of Artificial Intelligence: A Comprehensive Review.

Interdisciplinary sciences, computational life sciences
The recent COVID-19 pandemic, which broke at the end of the year 2019 in Wuhan, China, has infected more than 98.52 million people by today (January 23, 2021) with over 2.11 million deaths across the globe. To combat the growing pandemic on urgent ba...

Core services that power AI-driven transformation in cancer research and care.

Biochimica et biophysica acta. Reviews on cancer
This review captures some key lessons learned in the course of helping some of America's leading healthcare AI innovators achieve scale and sustained impact in complex research and care delivery ecosystems. AI innovators may find it useful to access ...

Machine Learning Generated Synthetic Faces for Use in Facial Aesthetic Research.

Facial plastic surgery & aesthetic medicine
A centralized repository of clinically applicable facial images with unrestricted use would facilitate facial aesthetic research. Using a machine learning neural network, we aim to (1) create a repository of synthetic faces that can be used for fac...

Biomedical Vibrational Spectroscopy in the Era of Artificial Intelligence.

Molecules (Basel, Switzerland)
Biomedical vibrational spectroscopy has come of age. The past twenty years have brought many advancements and new developments and now its practitioners face a new challenge: artificial intelligence. Artificial intelligence has the capability to dete...

Artificial intelligence in cancer research: learning at different levels of data granularity.

Molecular oncology
From genome-scale experimental studies to imaging data, behavioral footprints, and longitudinal healthcare records, the convergence of big data in cancer research and the advances in Artificial Intelligence (AI) is paving the way to develop a systems...