AIMC Topic: Humans

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CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis.

NMR in biomedicine
The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter-rater variability and the expenditure of time associated with manual assessment. We descr...

Comparing machine and human reviewers to evaluate the risk of bias in randomized controlled trials.

Research synthesis methods
BACKGROUND: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can...

An Introduction to Machine Learning.

Clinical pharmacology and therapeutics
In the last few years, machine learning (ML) and artificial intelligence have seen a new wave of publicity fueled by the huge and ever-increasing amount of data and computational power as well as the discovery of improved learning algorithms. However...

Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology?

Clinical pharmacology and therapeutics
As the field of artificial intelligence and machine learning (AI/ML) for drug discovery is rapidly advancing, we address the question "What is the impact of recent AI/ML trends in the area of Clinical Pharmacology?" We address difficulties and AI/ML ...

Collective effects of long-range DNA methylations predict gene expressions and estimate phenotypes in cancer.

Scientific reports
DNA methylation of various genomic regions has beenĀ found to be associated with gene expression in diverse biological contexts. However, most genome-wide studies have focused on the effect of (1) methylation in cis, not in trans and (2) a single CpG,...

AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining.

Scientific reports
The development of deep learning algorithms for complex tasks in digital medicine has relied on the availability of large labeled training datasets, usually containing hundreds of thousands of examples. The purpose of this study was to develop a 3D d...

Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data.

Nature communications
Chromatin interaction studies can reveal how the genome is organized into spatially confined sub-compartments in the nucleus. However, accurately identifying sub-compartments from chromatin interaction data remains a challenge in computational biolog...

An introduction to deep learning in medical physics: advantages, potential, and challenges.

Physics in medicine and biology
As one of the most popular approaches in artificial intelligence, deep learning (DL) has attracted a lot of attention in the medical physics field over the past few years. The goals of this topical review article are twofold. First, we will provide a...

Intracorporeal Studer Pouch Formation with Balbay's Technique Following Robotic Radical Cystectomy for Bladder Cancer: Experience with 22 Cases with Oncologic and Functional Outcomes.

Journal of endourology
Robot-assisted radical cystectomy (RARC) with intracorporeal Studer pouch formation (ICSPF) is increasingly being performed. Balbay's technique of ICSPF replicates the open approach with the additional advantages of inserting internal Double-J stent...