AIMC Topic: Humans

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Structural and functional brain networks of individual differences in trait anger and anger control: An unsupervised machine learning study.

The European journal of neuroscience
The ability to experience, use and eventually control anger is crucial to maintain well-being and build healthy relationships. Despite its relevance, the neural mechanisms behind individual differences in experiencing and controlling anger are poorly...

Identifying Cancer Subtypes Using a Residual Graph Convolution Model on a Sample Similarity Network.

Genes
Cancer subtype classification helps us to understand the pathogenesis of cancer and develop new cancer drugs, treatment from which patients would benefit most. Most previous studies detect cancer subtypes by extracting features from individual sample...

Composition-driven symptom phrase recognition for Chinese medical consultation corpora.

BMC medical informatics and decision making
BACKGROUND: Symptom phrase recognition is essential to improve the use of unstructured medical consultation corpora for the development of automated question answering systems. A majority of previous works typically require enough manually annotated ...

A Novel Deep Learning-Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Emergency department (ED) crowding has resulted in delayed patient treatment and has become a universal health care problem. Although a triage system, such as the 5-level emergency severity index, somewhat improves the process of ED treat...

Ensemble of Deep Learning Based Clinical Decision Support System for Chronic Kidney Disease Diagnosis in Medical Internet of Things Environment.

Computational intelligence and neuroscience
Recently, Internet of Things (IoT) and cloud computing environments become commonly employed in several healthcare applications by the integration of monitoring things such as sensors and medical gadgets for observing remote patients. For availing of...

A Rapid Artificial Intelligence-Based Computer-Aided Diagnosis System for COVID-19 Classification from CT Images.

Behavioural neurology
The excessive number of COVID-19 cases reported worldwide so far, supplemented by a high rate of false alarms in its diagnosis using the conventional polymerase chain reaction method, has led to an increased number of high-resolution computed tomogra...

Predicting individual task contrasts from resting-state functional connectivity using a surface-based convolutional network.

NeuroImage
Task-based and resting-state represent the two most common experimental paradigms of functional neuroimaging. While resting-state offers a flexible and scalable approach for characterizing brain function, task-based techniques provide superior locali...

Development of a radiomics and machine learning model for predicting occult cervical lymph node metastasis in patients with tongue cancer.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: We aimed to develop a predictive model for occult cervical lymph node metastasis in patients with tongue cancer using radiomics and machine learning from pretreatment contrast-enhanced computed tomography.

A multi-stage machine learning model for diagnosis of esophageal manometry.

Artificial intelligence in medicine
High-resolution manometry (HRM) is the primary procedure used to diagnose esophageal motility disorders. Its manual interpretation and classification, including evaluation of swallow-level outcomes and then derivation of a study-level diagnosis based...

Robotics, automation, active electrode arrays, and new devices for cochlear implantation: A contemporary review.

Hearing research
In the last two decades, cochlear implant surgery has evolved into a minimally invasive, hearing preservation surgical technique. The devices used during surgery have benefited from technological advances that have allowed modification and possible i...