FLEX-SMOTE: Synthetic over-sampling technique that flexibly adjusts to different minority class distributions.

Class imbalance is a challenge that affects the prediction rate on a minority class. To remedy this problem, various SMOTEs (synthetic minority over-sampling techniques) have been designed to populate synthetic minority instances. Some SMOTEs operate on the border of a minority class, while others concentrate on the class core.

Revolutionizing Grain and Particle Size Measurement in Metals: The Role of Sensor-Assisted Metallographic Image Analysis.

Metallographic image analysis is vital in the field of metal science due to its potential to automate the sensing process for grain and particle size estimation. To ensure the good quality and reliability of metal products, analysis of the integrity of metallic components is required. In contemporary manufacturing processes, microscopic analysis is a crucial step, mainly when complex systems like gearboxes, turbines, or engines are assembled using various components from multiple suppliers.

Influenza, dengue and common cold detection using LSTM with fully connected neural network and keywords selection.

Symptom-based machine learning models for disease detection are a way to reduce the workload of doctors when they have too many patients. Currently, there are many research studies on machine learning or deep learning for disease detection or clinical departments classification, using text of patient's symptoms and vital signs. In this study, we used the Long Short-term Memory (LSTM) with a fully connected neural network model for classification, where the LSTM model was used to receive the patient's symptoms text as input data.

mHealth Technology Translation in a Limited Resources Community-Process, Challenges, and Lessons Learned From a Limited Resources Community of Chiang Mai Province, Thailand.

This report aims to provide practical advice about the implementation of a public health monitoring system using both geographic information system technology and mobile health, a term used for healthcare delivery via mobile devices. application amongst household residents and community stakeholders in the limited resource community. A public health monitoring system was implemented in a semi-rural district in Thailand.

Bilateral pure facet joint dislocation in thoracolumbar junction (T11-T12) without facet fracture using a 3D digital printing model for surgical planning: A case report.

Background: Thoracolumbar junction pure bilateral facet joint dislocation without facet fracture is an extremely rare injury. A current review of thoracolumbar junction pure bilateral facet joint dislocation reported less than 15 cases in which the surgeon had a difficulty with the dissection of surgical planning using only 2D radiographic film and the axial or coronal view in computerized tomography. Bilateral pure facet joint dislocation in the thoracolumbar junction without facet fracture is difficult to understand the morphology of bone injuries.

Symptom-based data preprocessing for the detection of disease outbreak.

Early warning systems for outbreak detection is a challenge topic for researchers in the epidemiology and biomedical informatics fields. We are proposing a new method for detecting disease epidemics using a symptom-based approach. The data was collected from developed mobile applications which include users' demographic information and a list of chief complaint symptoms.