AIMC Topic: Humans

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Deep learning for improving PET/CT attenuation correction by elastic registration of anatomical data.

European journal of nuclear medicine and molecular imaging
BACKGROUND: For PET/CT, the CT transmission data are used to correct the PET emission data for attenuation. However, subject motion between the consecutive scans can cause problems for the PET reconstruction. A method to match the CT to the PET would...

The utility of machine learning for predicting donor discard in abdominal transplantation.

Clinical transplantation
BACKGROUND: Increasing access and better allocation of organs in the field of transplantation is a critical problem in clinical care. Limitations exist in accurately predicting allograft discard. Potential exists for machine learning to provide a bal...

Automatic Detection of Alzheimer's Disease using Deep Learning Models and Neuro-Imaging: Current Trends and Future Perspectives.

Neuroinformatics
Deep learning algorithms have a huge influence on tackling research issues in the field of medical image processing. It acts as a vital aid for the radiologists in producing accurate results toward effective disease diagnosis. The objective of this r...

A Federated Learning-Inspired Evolutionary Algorithm: Application to Glucose Prediction.

Sensors (Basel, Switzerland)
In this paper, we propose an innovative Federated Learning-inspired evolutionary framework. Its main novelty is that this is the first time that an Evolutionary Algorithm is employed on its own to directly perform Federated Learning activity. A furth...

IoT and Deep Learning-Based Farmer Safety System.

Sensors (Basel, Switzerland)
Farming is a fundamental factor driving economic development in most regions of the world. As in agricultural activity, labor has always been hazardous and can result in injury or even death. This perception encourages farmers to use proper tools, re...

Measurement and Processing of Thermographic Data of Passing Persons for Epidemiological Purposes.

Sensors (Basel, Switzerland)
Non-contact temperature measurement of persons during an epidemic is the most preferred measurement option because of the safety of personnel and minimal possibility of spreading infection. The use of infrared (IR) sensors to monitor building entranc...

A Novel IoT-Enabled Healthcare Monitoring Framework and Improved Grey Wolf Optimization Algorithm-Based Deep Convolution Neural Network Model for Early Diagnosis of Lung Cancer.

Sensors (Basel, Switzerland)
Lung cancer is a high-risk disease that causes mortality worldwide; nevertheless, lung nodules are the main manifestation that can help to diagnose lung cancer at an early stage, lowering the workload of radiologists and boosting the rate of diagnosi...

Diagnostic accuracy of AI in orthodontic extraction decisions: "Are we ready to let Mr. Data run our Enterprise?" A commentary on a systematic review.

Evidence-based dentistry
OBJECTIVE: To collect evidence on the ability of artificial intelligence programs to accurately make extraction decisions in orthodontic treatment planning.

Detection of malignancy in whole slide images of endometrial cancer biopsies using artificial intelligence.

PloS one
In this study we use artificial intelligence (AI) to categorise endometrial biopsy whole slide images (WSI) from digital pathology as either "malignant", "other or benign" or "insufficient". An endometrial biopsy is a key step in diagnosis of endomet...

Non-invasive regional cerebral blood flow quantification in the 123I-IMP autoradiography using artificial neural network.

PloS one
PURPOSE: Regional cerebral blood flow (rCBF) quantification using 123I-N-isopropyl-p-iodoamphetamine (123I-IMP) requires an invasive, one-time-only arterial blood sampling for measuring the 123I-IMP arterial blood radioactivity concentration (Ca10). ...