AIMC Topic: Machine Learning

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Comparing the Human Papillomavirus Vaccination Opinions Trends from Different Twitter User Groups with a Machine Learning Based System and Semiparametric Nonlinear Regression.

Studies in health technology and informatics
HPV vaccination refusal is a serious public health issue. Opinions on Twitter have are influential to potential consumers on vaccination behaviours. Public opinions toward HPV vaccination were extracted from Twitter by leveraging machine learning mod...

"Hybrid Topics" - Facilitating the Interpretation of Topics Through the Addition of MeSH Descriptors to Bags of Words.

Studies in health technology and informatics
Extracting and understanding information, themes and relationships from large collections of documents is an important task for biomedical researchers. Latent Dirichlet Allocation is an unsupervised topic modeling technique using the bag-of-words ass...

Applying Risk Models on Patients with Unknown Predictor Values: An Incremental Learning Approach.

Studies in health technology and informatics
In clinical practice, many patients may have unknown or missing values for some predictors, causing that the developed risk models cannot be directly applied on these patients. In this paper, we propose an incremental learning approach to apply a dev...

A Deep Learning-Based Method for Similar Patient Question Retrieval in Chinese.

Studies in health technology and informatics
The online patient question and answering (Q&A) system, either as a website or a mobile application, attracts an increasing number of users in China. Patients will post their questions and the registered doctors then provide the corresponding ans...

Development of a Deep Learning Algorithm for Automatic Diagnosis of Diabetic Retinopathy.

Studies in health technology and informatics
This paper mainly focuses on the deep learning application in classifying the stage of diabetic retinopathy and detecting the laterality of the eye using funduscopic images. Diabetic retinopathy is a chronic, progressive, sight-threatening disease of...

Using Machine Learning Models to Predict In-Hospital Mortality for ST-Elevation Myocardial Infarction Patients.

Studies in health technology and informatics
Acute myocardial infarction is a major cause of hospitalization and mortality in China, where ST-elevation myocardial infarction (STEMI) is more severe and has a higher mortality rate. Accurate and interpretable prediction of in-hospital mortality is...

Diagnostic Machine Learning Models for Acute Abdominal Pain: Towards an e-Learning Tool for Medical Students.

Studies in health technology and informatics
Computer-aided learning systems (e-learning systems) can help medical students gain more experience with diagnostic reasoning and decision making. Within this context, providing feedback that matches students' needs (i.e. personalised feedback) is bo...

Automatically Identifying Topics of Consumer Health Questions in Chinese.

Studies in health technology and informatics
In health question answering (QA) system development, question topic identification is crucial to understand users' information needs and further facilitate answer extraction. This paper presented a machine-learning method to automatically identify t...

General Symptom Extraction from VA Electronic Medical Notes.

Studies in health technology and informatics
There is need for cataloging signs and symptoms, but not all are documented in structured data. The text from clinical records are an additional source of signs and symptoms. We describe a Natural Language Processing (NLP) technique to identify sympt...

Automatic Identification of Glaucoma Using Deep Learning Methods.

Studies in health technology and informatics
This paper proposes an automatic classification method to detect glaucoma in fundus images. The method is based on training a neural network using public image databases. The network used in this paper is the GoogLeNet, adapted for this proposal. The...