AIMC Topic: Humans

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Performance Assessment of Classification Algorithms on Early Detection of Liver Syndrome.

Journal of healthcare engineering
In the recent era, a liver syndrome that causes any damage in life capacity is exceptionally normal everywhere throughout the world. It has been found that liver disease is exposed more in young people as a comparison with other aged people. At the p...

Detection of Snore from OSAHS Patients Based on Deep Learning.

Journal of healthcare engineering
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is extremely harmful to the human body and may cause neurological dysfunction and endocrine dysfunction, resulting in damage to multiple organs and multiple systems throughout the body and negatively ...

Continuous Similarity Learning with Shared Neural Semantic Representation for Joint Event Detection and Evolution.

Computational intelligence and neuroscience
In the era of the rapid development of today's Internet, people often feel overwhelmed by vast official news streams or unofficial self-media tweets. To help people obtain the news topics they care about, there is a growing need for systems that can ...

One of the first validations of an artificial intelligence algorithm for clinical use: The impact on intraoperative hypotension prediction and clinical decision-making.

Surgery
This review describes the steps and conclusions from the development and validation of an artificial intelligence algorithm (the Hypotension Prediction Index), one of the first machine learning predictive algorithms used in the operating room environ...

Identification the source of fecal contamination for geographically unassociated samples with a statistical classification model based on support vector machine.

Journal of hazardous materials
The bacterial diversity and corresponding biological significance revealed by high-throughput sequencing contribute massive information to source tracking of fecal contamination. The performances of classification models on predicting the fecal sourc...

Milestones for autonomous in vivo microrobots in medical applications.

Surgery
In light of recent developments within both health care and robotics, the use of robots within the human body has become attainable. Here we discuss the milestones for the realization of autonomous microrobots in medical applications. The desired tas...

Artificial intelligence in the diagnosis of pediatric allergic diseases.

Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology
Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self-care, prevention and wellness, clinical decisi...

Daily urine loss immediately after urethral catheter removal may be an effective predictor of long-term urinary incontinence following robot-assisted laparoscopic radical prostatectomy.

International journal of clinical practice
PURPOSE: Some patients who undergo robot-assisted laparoscopic radical prostatectomy (RARP) continue to experience long-term urinary incontinence (UI). This study aimed to evaluate easily obtainable factors that can predict long-term UI following RAR...

3D deep learning based classification of pulmonary ground glass opacity nodules with automatic segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Classifying ground-glass lung nodules (GGNs) into atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) on diagnostic CT images is important to evaluate the th...

Deep learning powers cancer diagnosis in digital pathology.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Technological innovation has accelerated the pathological diagnostic process for cancer, especially in digitizing histopathology slides and incorporating deep learning-based approaches to mine the subvisual morphometric phenotypes for improving patho...