AIMC Topic: Humans

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A case study of lean digital transformation through robotic process automation in healthcare.

Scientific reports
Under Taiwan's National Health Insurance (NHI) system, it's crucial for all healthcare providers to accurately submit medical expense claims to the National Health Insurance Administration (NHIA) to avoid incorrect deductions. With changes in healthc...

AI nutrition recommendation using a deep generative model and ChatGPT.

Scientific reports
In recent years, major advances in artificial intelligence (AI) have led to the development of powerful AI systems for use in the field of nutrition in order to enhance personalized dietary recommendations and improve overall health and well-being. H...

Machine Learning-Enhanced Extraction of Biomarkers for High-Grade Serous Ovarian Cancer from Proteomics Data.

Scientific data
Comprehensive biomedical proteomic datasets are accumulating exponentially, warranting robust analytics to deconvolute them for identifying novel biological insights. Here, we report a strategic machine learning (ML)-based feature extraction workflow...

Deep learning model for the prediction of all-cause mortality among long term care people in China: a prospective cohort study.

Scientific reports
This study aimed to develop a deep learning model to predict the risk stratification of all-cause death for older people with disability, providing guidance for long-term care plans. Based on the government-led long-term care insurance program in a p...

Predicting type 2 diabetes via machine learning integration of multiple omics from human pancreatic islets.

Scientific reports
Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the mechanisms behind this defect are insufficiently characterized. Integrating multiple la...

Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery.

Nature communications
Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a promising alternative to target-based methods, overcoming limitations like lack of well-defined targets. While chemical-induced transcriptional profiles ...

Analysis of factors that indicated surgery in 400 patients submitted to a complete diagnostic workup for obstructed defecation syndrome and rectal prolapse using a supervised machine learning algorithm.

Techniques in coloproctology
BACKGROUND: Patient selection is extremely important in obstructed defecation syndrome (ODS) and rectal prolapse (RP) surgery. This study assessed factors that guided the indications for ODS and RP surgery and their specific role in our decision-maki...

An automated in vitro wound healing microscopy image analysis approach utilizing U-net-based deep learning methodology.

BMC medical imaging
BACKGROUND: The assessment of in vitro wound healing images is critical for determining the efficacy of the therapy-of-interest that may influence the wound healing process. Existing methods suffer significant limitations, such as user dependency, ti...

Binary classification of dead detector elements in flat panel detectors using convolutional neural networks.

Biomedical physics & engineering express
Medical physicists routinely perform quality assurance on digital detection systems, part of which involves the testing of flat panel detectors. Flat panels may degrade over time as an increasing number of individual detector elements begin to malfun...