AIMC Topic: Humans

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Artificial intelligence in detection and segmentation of internal auditory canal and its nerves using deep learning techniques.

International journal of computer assisted radiology and surgery
PURPOSE: Artificial intelligence (AI) in medical imaging is a burgeoning topic that involves the interpretation of complex image structures. The recent advancements in deep learning techniques increase the computational powers to extract vital featur...

REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.

Molecular genetics & genomic medicine
BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an...

Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency.

AJR. American journal of roentgenology
The objective of our study was to systematically review the literature about the application of artificial intelligence (AI) to renal mass characterization with a focus on the methodologic quality items. A systematic literature search was conducted...

Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation.

The Lancet. Digital health
BACKGROUND: Prompt identification of patients suspected to have COVID-19 is crucial for disease control. We aimed to develop a deep learning algorithm on the basis of chest CT for rapid triaging in fever clinics.

Unveiling COVID-19 from CHEST X-Ray with Deep Learning: A Hurdles Race with Small Data.

International journal of environmental research and public health
The possibility to use widespread and simple chest X-ray (CXR) imaging for early screening of COVID-19 patients is attracting much interest from both the clinical and the AI community. In this study we provide insights and also raise warnings on what...

Tracking historical changes in trustworthiness using machine learning analyses of facial cues in paintings.

Nature communications
Social trust is linked to a host of positive societal outcomes, including improved economic performance, lower crime rates and more inclusive institutions. Yet, the origins of trust remain elusive, partly because social trust is difficult to document...

Identification of risk features for complication in Gaucher's disease patients: a machine learning analysis of the Spanish registry of Gaucher disease.

Orphanet journal of rare diseases
BACKGROUND: Since enzyme replacement therapy for Gaucher disease (MIM#230800) has become available, both awareness of and the natural history of the disease have changed. However, there remain unmet needs such as the identification of patients at ris...

A data-driven approach to a chemotherapy recommendation model based on deep learning for patients with colorectal cancer in Korea.

BMC medical informatics and decision making
BACKGROUND: Clinical Decision Support Systems (CDSSs) have recently attracted attention as a method for minimizing medical errors. Existing CDSSs are limited in that they do not reflect actual data. To overcome this limitation, we propose a CDSS base...

An embedded gene selection method using knockoffs optimizing neural network.

BMC bioinformatics
BACKGROUND: Gene selection refers to find a small subset of discriminant genes from the gene expression profiles. How to select genes that affect specific phenotypic traits effectively is an important research work in the field of biology. The neural...