AIMC Topic: Humans

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Face Manipulation Detection Based on Supervised Multi-Feature Fusion Attention Network.

Sensors (Basel, Switzerland)
Nowadays, faces in videos can be easily replaced with the development of deep learning, and these manipulated videos are realistic and cannot be distinguished by human eyes. Some people maliciously use the technology to attack others, especially cele...

A Reliable and Efficient Tracking System Based on Deep Learning for Monitoring the Spread of COVID-19 in Closed Areas.

International journal of environmental research and public health
Since 2020, the world is still facing a global economic and health crisis due to the COVID-19 pandemic. One approach to fighting this global crisis is to track COVID-19 cases by wireless technologies, which requires receiving reliable, efficient, and...

Predicting anesthetic infusion events using machine learning.

Scientific reports
Recently, research has been conducted to automatically control anesthesia using machine learning, with the aim of alleviating the shortage of anesthesiologists. In this study, we address the problem of predicting decisions made by anesthesiologists d...

Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions.

Scientific reports
Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase may help medical doctors to make better decisions. DR is considered one of the main risks, leading t...

ACP-MHCNN: an accurate multi-headed deep-convolutional neural network to predict anticancer peptides.

Scientific reports
Although advancing the therapeutic alternatives for treating deadly cancers has gained much attention globally, still the primary methods such as chemotherapy have significant downsides and low specificity. Most recently, Anticancer peptides (ACPs) h...

An early model to predict the risk of gestational diabetes mellitus in the absence of blood examination indexes: application in primary health care centres.

BMC pregnancy and childbirth
BACKGROUND: Gestational diabetes mellitus (GDM) is one of the critical causes of adverse perinatal outcomes. A reliable estimate of GDM in early pregnancy would facilitate intervention plans for maternal and infant health care to prevent the risk of ...

Identifying and evaluating clinical subtypes of Alzheimer's disease in care electronic health records using unsupervised machine learning.

BMC medical informatics and decision making
BACKGROUND: Alzheimer's disease (AD) is a highly heterogeneous disease with diverse trajectories and outcomes observed in clinical populations. Understanding this heterogeneity can enable better treatment, prognosis and disease management. Studies to...

Pneumoconiosis computer aided diagnosis system based on X-rays and deep learning.

BMC medical imaging
PURPOSE: The objective of this study is to construct a computer aided diagnosis system for normal people and pneumoconiosis using X-raysand deep learning algorithms.

Tinnitus-like "hallucinations" elicited by sensory deprivation in an entropy maximization recurrent neural network.

PLoS computational biology
Sensory deprivation has long been known to cause hallucinations or "phantom" sensations, the most common of which is tinnitus induced by hearing loss, affecting 10-20% of the population. An observable hearing loss, causing auditory sensory deprivatio...

MSTCN: A multiscale temporal convolutional network for user independent human activity recognition.

F1000Research
In recent years, human activity recognition (HAR) has been an active research topic due to its widespread application in various fields such as healthcare, sports, patient monitoring, etc. HAR approaches can be categorised as handcrafted feature met...