AIMC Topic: Artificial Intelligence

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Artificial intelligence-driven phenotyping of zebrafish psychoactive drug responses.

Progress in neuro-psychopharmacology & biological psychiatry
Zebrafish (Danio rerio) are rapidly emerging in biomedicine as promising tools for disease modelling and drug discovery. The use of zebrafish for neuroscience research is also growing rapidly, necessitating novel reliable and unbiased methods of neur...

Intelligent Network Applications Monitoring and Diagnosis Employing Software Sensing and Machine Learning Solutions.

Sensors (Basel, Switzerland)
The article presents a research in the field of complex sensing, detection, and recovery of communications networks applications and hardware, in case of failures, maloperations, or unauthorized intrusions. A case study, based on Davis AI engine oper...

Needs for re-intervention on restored teeth in adults: a practice-based study.

Clinical oral investigations
OBJECTIVES: Evaluate the need for re-intervention on dental coronal restorations in adults seen in a network of general dental practitioners (ReCOL).  MATERIALS AND METHODS: This observational, cross-sectional, multicenter study involved 40 practitio...

Three artificial intelligence data challenges based on CT and ultrasound.

Diagnostic and interventional imaging
PURPOSE: The 2020 edition of these Data Challenges was organized by the French Society of Radiology (SFR), from September 28 to September 30, 2020. The goals were to propose innovative artificial intelligence solutions for the current relevant proble...

Artificial Intelligence-Enabled Electrocardiography to Screen Patients with Dilated Cardiomyopathy.

The American journal of cardiology
Undiagnosed dilated cardiomyopathy (DC) can be asymptomatic or present as sudden cardiac death, therefore pre-emptively identifying and treating patients may be beneficial. Screening for DC with echocardiography is expensive and labor intensive and s...

Detection of segmented uterine cancer images by Hotspot Detection method using deep learning models, Pigeon-Inspired Optimization, types-based dominant activation selection approaches.

Computers in biology and medicine
Uterine cancer consists of cells of a layer that forms the inside of the uterus. Sometimes, as a result of abnormal growth of normal cells, it can damage the surrounding tissues and cause the formation of cancerous cells. In the USA, according to the...

Disruptive innovations in the clinical laboratory: catching the wave of precision diagnostics.

Critical reviews in clinical laboratory sciences
Disruptive innovation is an invention that disrupts an existing market and creates a new one by providing a different set of values, which ultimately overtakes the existing market. Typically, when disruptive innovations are introduced, their performa...

Production of biofuels from biomass: Predicting the energy employing artificial intelligence modelling.

Bioresource technology
Bioenergy may be a major replacement of fossil fuels which can make the path easier for sustainable development and decrease the dependency on conventional sources of energy. The main concern with the bioenergy is the availability of feedstock, deali...

Electrocardiogram-Based Emotion Recognition Systems and Their Applications in Healthcare-A Review.

Sensors (Basel, Switzerland)
Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or device with affective computing is beneficial for the mental health and wellbeing of individuals that...

Rebirth of Distributed AI-A Review of eHealth Research.

Sensors (Basel, Switzerland)
The envisioned smart city domains are expected to rely heavily on artificial intelligence and machine learning (ML) approaches for their operations, where the basic ingredient is data. Privacy of the data and training time have been major roadblocks ...