AI Medical Compendium Topic

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A data driven methodology for social science research with left-behind children as a case study.

PloS one
For decades, traditional correlation analysis and regression models have been used in social science research. However, the development of machine learning algorithms makes it possible to apply machine learning techniques for social science research ...

Integrating a Machine Learning System Into Clinical Workflows: Qualitative Study.

Journal of medical Internet research
BACKGROUND: Machine learning models have the potential to improve diagnostic accuracy and management of acute conditions. Despite growing efforts to evaluate and validate such models, little is known about how to best translate and implement these pr...

Integrating Mobile Robots into Automated Laboratory Processes: A Suitable Workflow Management System.

SLAS technology
The general trend of automation is currently increasing in life science laboratories. The samples to be examined show a high diversity in their structures and composition as well as the determination methods. Complex automation lines such as those us...

Development and evaluation of a deep learning based artificial intelligence for automatic identification of gold fiducial markers in an MRI-only prostate radiotherapy workflow.

Physics in medicine and biology
Identification of prostate gold fiducial markers in magnetic resonance imaging (MRI) images is challenging when CT images are not available, due to misclassifications from intra-prostatic calcifications. It is also a time consuming task and automated...

Radiomics in PET/CT: Current Status and Future AI-Based Evolutions.

Seminars in nuclear medicine
This short review aims at providing the readers with an update on the current status, as well as future perspectives in the quickly evolving field of radiomics applied to the field of PET/CT imaging. Numerous pitfalls have been identified in study de...

Profiling SARS-CoV-2 Main Protease (M) Binding to Repurposed Drugs Using Molecular Dynamics Simulations in Classical and Neural Network-Trained Force Fields.

ACS combinatorial science
The current COVID-19 pandemic caused by a novel coronavirus SARS-CoV-2 urgently calls for a working therapeutic. Here, we report a computation-based workflow for efficiently selecting a subset of FDA-approved drugs that can potentially bind to the SA...

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...

Reducing annotation effort in digital pathology: A Co-Representation learning framework for classification tasks.

Medical image analysis
Classification of digital pathology images is imperative in cancer diagnosis and prognosis. Recent advancements in deep learning and computer vision have greatly benefited the pathology workflow by developing automated solutions for classification ta...

CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence.

EBioMedicine
BACKGROUND: Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's pr...

Blockchain in Healthcare: Insights on COVID-19.

International journal of environmental research and public health
The SARS-CoV2 pandemic has impacted risk management globally. Blockchain has been increasingly applied to healthcare management, as a strategic tool to strengthen operative protocols and to create the proper basis for an efficient and effective evide...