AIMC Topic: Humans

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Feasibility of a Real-Time Clinical Augmented Reality and Artificial Intelligence Framework for Pain Detection and Localization From the Brain.

Journal of medical Internet research
BACKGROUND: For many years, clinicians have been seeking for objective pain assessment solutions via neuroimaging techniques, focusing on the brain to detect human pain. Unfortunately, most of those techniques are not applicable in the clinical envir...

Respiratory Sound Based Classification of Chronic Obstructive Pulmonary Disease: a Risk Stratification Approach in Machine Learning Paradigm.

Journal of medical systems
This article investigates the classification of normal and COPD subjects on the basis of respiratory sound analysis using machine learning techniques. Thirty COPD and 25 healthy subject data are recorded. Total of 39 lung sound features and 3 spirome...

Improved Deep Learning Network Based in combination with Cost-sensitive Learning for Early Detection of Ovarian Cancer in Color Ultrasound Detecting System.

Journal of medical systems
With the development of theories and technologies in medical imaging, most of the tumors can be detected in the early stage. However, the nature of ovarian cysts lacks accurate judgement, leading to that many patients with benign nodules still need F...

A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization.

Journal of medical systems
The aim of this study is to predict acute coronary syndrome (ACS) requiring revascularization in those patients presenting early-stage angina-like symptom using machine learning algorithms. We obtained data from 2344 ACS patients, who required revasc...

Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters.

Environmental monitoring and assessment
Approximately 50 million Americans have allergic diseases. Airborne plant pollen is a significant trigger for several of these allergic diseases. Ambrosia (ragweed) is known for its abundant production of pollen and its potent allergic effect in Nort...

Determination of the physical domain for air quality monitoring stations using the ANP-OWA method in GIS.

Environmental monitoring and assessment
Air pollution is a major concern in some megacities of Iran. Specific cities in the country have reached an extremely harmful level of air pollution which poses a serious risk to the daily lives of Iranians. According to news reports, the air quality...

Using machine learning to examine the relationship between asthma and absenteeism.

Environmental monitoring and assessment
In this study, we found that machine learning was able to effectively estimate student learning outcomes geo-spatially across all the campuses in a large, urban, independent school district. The machine learning showed that key factors in estimating ...

Using machine learning to understand the temporal morphology of the PM annual cycle in East Asia.

Environmental monitoring and assessment
PM air pollution is a significant issue for human health all over the world, especially in East Asia. A large number of ground-based measurement sites have been established over the last decade to monitor real-time PM concentration. However, even thi...

A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS).

Nature communications
Cell state-specific promoters constitute essential tools for basic research and biotechnology because they activate gene expression only under certain biological conditions. Synthetic Promoters with Enhanced Cell-State Specificity (SPECS) can be supe...

Outcome measurement in mental health services: insights from symptom networks.

BMC psychiatry
BACKGROUND: In mental health, outcomes are currently measured by changes of individual scores. However, such an analysis on individual scores does not take into account the interaction between symptoms, which could yield crucial information while inv...