AIMC Topic: Humans

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Attention Autoencoder for Generative Latent Representational Learning in Anomaly Detection.

Sensors (Basel, Switzerland)
Today, accurate and automated abnormality diagnosis and identification have become of paramount importance as they are involved in many critical and life-saving scenarios. To accomplish such frontiers, we propose three artificial intelligence models ...

Development of a prediction score for in-hospital mortality in COVID-19 patients with acute kidney injury: a machine learning approach.

Scientific reports
Acute kidney injury (AKI) is frequently associated with COVID-19 and it is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting in-hospital mortality in COVID-19 patients with AKI (AKI-COV score)....

A review on deep learning MRI reconstruction without fully sampled k-space.

BMC medical imaging
BACKGROUND: Magnetic resonance imaging (MRI) is an effective auxiliary diagnostic method in clinical medicine, but it has always suffered from the problem of long acquisition time. Compressed sensing and parallel imaging are two common techniques to ...

Deep learning reveals personalized spatial spectral abnormalities of high delta and low alpha bands in EEG of patients with early Parkinson's disease.

Journal of neural engineering
Parkinson's disease (PD) is one of the most common neurodegenerative diseases, and early diagnosis is crucial to delay disease progression. The diagnosis of early PD has always been a difficult clinical problem due to the lack of reliable biomarkers....

Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare.

Current medical science
Chronic diseases are a growing concern worldwide, with nearly 25% of adults suffering from one or more chronic health conditions, thus placing a heavy burden on individuals, families, and healthcare systems. With the advent of the "Smart Healthcare" ...

Back Propagation Neural Network-Based Magnetic Resonance Imaging Image Features in Treating Intestinal Obstruction in Digestive Tract Diseases with Chengqi Decoction.

Contrast media & molecular imaging
This study was to explore the adoption effect of magnetic resonance imaging (MRI) image features based on back propagation neural network (BPNN) in evaluating the curative effect of Chengqi Decoction (CD) for intestinal obstruction (ileus), so as to ...

Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students' Perception.

Frontiers in public health
The emerging field of artificial intelligence (AI) will probably affect the practice for the next generation of doctors. However, the students' views on AI have not been largely investigated. An anonymous electronic survey on AI was designed for me...

Deep-Learning-Based Survival Prediction of Patients in Coronary Care Units.

Computational and mathematical methods in medicine
BACKGROUND: A survival prediction model based on deep learning has higher accuracy than the CPH model in predicting the survival of CCU patients, and it also has a better discrimination ability. We collected information on patients with various disea...

[Ocular changes as a diagnostic tool for malaria].

Die Ophthalmologie
BACKGROUND: According to the WHO Malaria Report 2019 a total of 229 million people fall ill with malaria each year and two thirds of deaths involve children under 5 years of age.

DiversityScanner: Robotic handling of small invertebrates with machine learning methods.

Molecular ecology resources
Invertebrate biodiversity remains poorly understood although it comprises much of the terrestrial animal biomass, most species and supplies many ecosystem services. The main obstacle is specimen-rich samples obtained with quantitative sampling techni...