AIMC Topic: Data Collection

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Citation screening using crowdsourcing and machine learning produced accurate results: Evaluation of Cochrane's modified Screen4Me service.

Journal of clinical epidemiology
OBJECTIVES: To assess the feasibility of a modified workflow that uses machine learning and crowdsourcing to identify studies for potential inclusion in a systematic review.

Tianxia120: A Multimodal Medical Data Collection Bioinformatic System for Proactive Health Management in Internet of Medical Things.

Journal of healthcare engineering
A digital medical health system named Tianxia120 that can provide patients and hospitals with "one-step service" is proposed in this paper. Evolving from the techniques of Internet of Medical Things (IoMT), medical dig data, and medical Artificial In...

A detection method for android application security based on TF-IDF and machine learning.

PloS one
Android is the most widely used mobile operating system (OS). A large number of third-party Android application (app) markets have emerged. The absence of third-party market regulation has prompted research institutions to propose different malware d...

Neural Network-Based Study about Correlation Model between TCM Constitution and Physical Examination Indexes Based on 950 Physical Examinees.

Journal of healthcare engineering
PURPOSE: To establish the correlation model between Traditional Chinese Medicine (TCM) constitution and physical examination indexes by backpropagation neural network (BPNN) technology. A new method for the identification of TCM constitution in clini...

Social Network Analysis of COVID-19 Sentiments: Application of Artificial Intelligence.

Journal of medical Internet research
BACKGROUND: The coronavirus disease (COVID-19) pandemic led to substantial public discussion. Understanding these discussions can help institutions, governments, and individuals navigate the pandemic.

Improving the accuracy of medical diagnosis with causal machine learning.

Nature communications
Machine learning promises to revolutionize clinical decision making and diagnosis. In medical diagnosis a doctor aims to explain a patient's symptoms by determining the diseases causing them. However, existing machine learning approaches to diagnosis...

Opportunities and challenges in the collection and analysis of digital phenotyping data.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
The broad adoption and use of smartphones has led to fundamentally new opportunities for capturing social, behavioral, and cognitive phenotypes in free-living settings, outside of research laboratories and clinics. Predicated on the use of existing p...

Efficient mapping of crash risk at intersections with connected vehicle data and deep learning models.

Accident; analysis and prevention
Traditional methods for identifying crash-prone roadways are mainly based on historical crash data. It usually requires more than three years to collect a sufficient amount of dataset for road safety assessment. However, the emerging connected vehicl...

Intelligent animal detection system using sparse multi discriminative-neural network (SMD-NN) to mitigate animal-vehicle collision.

Environmental science and pollution research international
Animal-Vehicle Collision (AVC) is a predominant problem in both urban and rural roads and highways. Detecting animals on the road is challenging due to factors like the fast movement of both animals and vehicles, highly cluttered environmental settin...