AIMC Topic: Humans

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Deep learning-enabled imaging flow cytometry for high-speed Cryptosporidium and Giardia detection.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Imaging flow cytometry has become a popular technology for bioparticle image analysis because of its capability of capturing thousands of images per second. Nevertheless, the vast number of images generated by imaging flow cytometry imposes great cha...

Weakly supervised deep learning for determining the prognostic value of F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type.

European journal of nuclear medicine and molecular imaging
PURPOSE: To develop a weakly supervised deep learning (WSDL) method that could utilize incomplete/missing survival data to predict the prognosis of extranodal natural killer/T cell lymphoma, nasal type (ENKTL) based on pretreatment F-FDG PET/CT resul...

The integration of artificial intelligence in medical imaging practice: Perspectives of African radiographers.

Radiography (London, England : 1995)
INTRODUCTION: The current technological developments in medical imaging are centred largely on the increasing integration of artificial intelligence (AI) into all equipment modalities. This survey assessed the perspectives of African radiographers on...

Deep-learning system for real-time differentiation between Crohn's disease, intestinal Behçet's disease, and intestinal tuberculosis.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Pattern analysis of big data can provide a superior direction for the clinical differentiation of diseases with similar endoscopic findings. This study aimed to develop a deep-learning algorithm that performs differential diagnosi...

Machine learning-based cytokine microarray digital immunoassay analysis.

Biosensors & bioelectronics
Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short ...

Predicting presumed serious infection among hospitalized children on central venous lines with machine learning.

Computers in biology and medicine
BACKGROUND: Presumed serious infection (PSI) is defined as a blood culture drawn and new antibiotic course of at least 4 days among pediatric patients with Central Venous Lines (CVLs). Early PSI prediction and use of medical interventions can prevent...

Artificial intelligence in cancer research: learning at different levels of data granularity.

Molecular oncology
From genome-scale experimental studies to imaging data, behavioral footprints, and longitudinal healthcare records, the convergence of big data in cancer research and the advances in Artificial Intelligence (AI) is paving the way to develop a systems...

COVID-19 Detection from Chest X-ray Images Using Feature Fusion and Deep Learning.

Sensors (Basel, Switzerland)
Currently, COVID-19 is considered to be the most dangerous and deadly disease for the human body caused by the novel coronavirus. In December 2019, the coronavirus spread rapidly around the world, thought to be originated from Wuhan in China and is r...

A Classification Method for the Cellular Images Based on Active Learning and Cross-Modal Transfer Learning.

Sensors (Basel, Switzerland)
In computer-aided diagnosis (CAD) systems, the automatic classification of the different types of the human epithelial type 2 (HEp-2) cells represents one of the critical steps in the diagnosis procedure of autoimmune diseases. Most of the methods pr...