AIMC Topic: Humans

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Deep learning in next-generation sequencing.

Drug discovery today
Next-generation sequencing (NGS) methods lie at the heart of large parts of biological and medical research. Their fundamental importance has created a continuously increasing demand for processing and analysis methods of the data sets produced, addr...

Artificial Intelligence in Screening Mammography: A Population Survey of Women's Preferences.

Journal of the American College of Radiology : JACR
OBJECTIVE: To investigate the general population's view on the use of artificial intelligence (AI) for the diagnostic interpretation of screening mammograms.

Clinical and laboratory data, radiological structured report findings and quantitative evaluation of lung involvement on baseline chest CT in COVID-19 patients to predict prognosis.

La Radiologia medica
OBJECTIVE: To evaluate by means of regression models the relationships between baseline clinical and laboratory data and lung involvement on baseline chest CT and to quantify the thoracic disease using an artificial intelligence tool and a visual sco...

Identification of an epigenetic signature in human induced pluripotent stem cells using a linear machine learning model.

Human cell
The use of human induced pluripotent stem cells (iPSCs), used as an alternative to human embryonic stem cells (ESCs), is a potential solution to challenges, such as immune rejection, and does not involve the ethical issues concerning the use of ESCs ...

Precision Medicine, AI, and the Future of Personalized Health Care.

Clinical and translational science
The convergence of artificial intelligence (AI) and precision medicine promises to revolutionize health care. Precision medicine methods identify phenotypes of patients with less-common responses to treatment or unique healthcare needs. AI leverages ...

Machine Learning Improves the Identification of Individuals With Higher Morbidity and Avoidable Health Costs After Acute Coronary Syndromes.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Traditional risk scores improved the definition of the initial therapeutic strategy in acute coronary syndrome (ACS), but they were not designed for predicting long-term individual risks and costs. In parallel, attempts to directly predic...

Predicting 3D genome folding from DNA sequence with Akita.

Nature methods
In interphase, the human genome sequence folds in three dimensions into a rich variety of locus-specific contact patterns. Cohesin and CTCF (CCCTC-binding factor) are key regulators; perturbing the levels of either greatly disrupts genome-wide foldin...

DeepC: predicting 3D genome folding using megabase-scale transfer learning.

Nature methods
Predicting the impact of noncoding genetic variation requires interpreting it in the context of three-dimensional genome architecture. We have developed deepC, a transfer-learning-based deep neural network that accurately predicts genome folding from...

Clearness of operating field: a surrogate for surgical skills on in vivo clinical data.

International journal of computer assisted radiology and surgery
PURPOSE: Automatic surgical skill assessment is an emerging field beneficial to both efficiency and quality of surgical education and practice. Prior works largely evaluate skills on elementary tasks performed in the simulation laboratory, which cann...