AIMC Topic: Humans

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High-accuracy morphological identification of bone marrow cells using deep learning-based Morphogo system.

Scientific reports
Accurate identification and classification of bone marrow (BM) nucleated cell morphology are crucial for the diagnosis of hematological diseases. However, the subjective and time-consuming nature of manual identification by pathologists hinders promp...

Development and validation of a hybrid deep learning-machine learning approach for severity assessment of COVID-19 and other pneumonias.

Scientific reports
The Coronavirus Disease 2019 (COVID-19) is transitioning into the endemic phase. Nonetheless, it is crucial to remain mindful that pandemics related to infectious respiratory diseases (IRDs) can emerge unpredictably. Therefore, we aimed to develop an...

Cohort profile for development of machine learning models to predict healthcare-related adverse events (Demeter): clinical objectives, data requirements for modelling and overview of data set for 2016-2018.

BMJ open
PURPOSE: In-hospital health-related adverse events (HAEs) are a major concern for hospitals worldwide. In high-income countries, approximately 1 in 10 patients experience HAEs associated with their hospital stay. Estimating the risk of an HAE at the ...

Deep learning-based dose map prediction for high-dose-rate brachytherapy.

Physics in medicine and biology
. Creating a clinically acceptable plan in the time-sensitive clinic workflow of brachytherapy is challenging. Deep learning-based dose prediction techniques have been reported as promising solutions with high efficiency and accuracy. However, curren...

The current role and evolution of X-ray crystallography in drug discovery and development.

Expert opinion on drug discovery
INTRODUCTION: Macromolecular X-ray crystallography and cryo-EM are currently the primary techniques used to determine the three-dimensional structures of proteins, nucleic acids, and viruses. Structural information has been critical to drug discovery...

Automatic detection and classification of lung cancer CT scans based on deep learning and ebola optimization search algorithm.

PloS one
Recently, research has shown an increased spread of non-communicable diseases such as cancer. Lung cancer diagnosis and detection has become one of the biggest obstacles in recent years. Early lung cancer diagnosis and detection would reliably promot...

Systematic review of artificial intelligence development and evaluation for MRI diagnosis of knee ligament or meniscus tears.

Skeletal radiology
OBJECTIVE: The purpose of this systematic review was to summarize the results of original research studies evaluating the characteristics and performance of deep learning models for detection of knee ligament and meniscus tears on MRI.

Smartphone Eye Examination: Artificial Intelligence and Telemedicine.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
The current medical scenario is closely linked to recent progress in telecommunications, photodocumentation, and artificial intelligence (AI). Smartphone eye examination may represent a promising tool in the technological spectrum, with special inte...

Comparative evaluation of uncertainty estimation and decomposition methods on liver segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: Deep neural networks need to be able to indicate error likelihood via reliable estimates of their predictive uncertainty when used in high-risk scenarios, such as medical decision support. This work contributes a systematic overview of state...

Circulating Biomarkers Instead of Genotyping to Establish Metabolizer Phenotypes.

Annual review of pharmacology and toxicology
Pharmacogenomics (PGx) enables personalized treatment for the prediction of drug response and to avoid adverse drug reactions. Currently, PGx mainly relies on the genetic information of absorption, distribution, metabolism, and excretion (ADME) targe...