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A Quantitative Assessment of Time, Frequency, and Time-frequency Algorithms for Automated Seizure Detection and Monitoring

Vangal et al. | Sep 28, 2020

A Quantitative Assessment of Time, Frequency, and Time-frequency Algorithms for Automated Seizure Detection and Monitoring

Each year, over 100,000 patients die from Sudden Unexpected Death in Epilepsy (SUDEP). A reliable seizure warning system can help patients stay safe. This work presents a comprehensive, comparative analysis of three different signal processing algorithms for automated seizure/ictal detection. The experimental results show that the proposed methods can be effective for accurate automated seizure detection and monitoring in clinical care.

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Culturally Adapted Assessment Tool for Autism Spectrum Disorder and its Clinical Significance

Das et al. | Apr 19, 2021

Culturally Adapted Assessment Tool for Autism Spectrum Disorder and its Clinical Significance

Diagnosing of Autism Spectrum Disorder (ASD) using tools developed in the West is challenging in the Indian setting due to a huge diversity in sociocultural and economic backgrounds. Here, the authors developed a home-based, audiovisual game app (Autest) suitable for ASD risk assessment in Indian children under 10 years of age. Ratings suggested that the tool is effective and can reduce social inhibition and facilitate assessment. Further usage and development of Autest can improve risk assessment and early intervention measures for children with ASD in India.

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QuitPuff: A Simple Method Using Saliva to Assess the Risk of Oral Pre-Cancerous Lesions and Oral Squamous Cell Carcinoma in Chronic Smokers

Shamsher et al. | Mar 27, 2019

QuitPuff: A Simple Method Using Saliva to Assess the Risk of Oral Pre-Cancerous Lesions and Oral Squamous Cell Carcinoma in Chronic Smokers

Smoking generates free radicals and reactive oxygen species which induce cell damage and lipid peroxidation. This is linked to the development of oral cancer in chronic smokers. The authors of this study developed Quitpuff, simple colorimetric test to measure the extent of lipid peroxidation in saliva samples. This test detected salivary lipid peroxidation with 96% accuracy in test subjects and could serve as an inexpensive, non-invasive test for smokers to measure degree of salivary lipid peroxidation and potential risk of oral cancer.

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Who is at Risk for a Spinal Fracture? – A Comparative Study of National Health and Nutrition Examination Survey Data

He et al. | Mar 01, 2018

Who is at Risk for a Spinal Fracture? – A Comparative Study of National Health and Nutrition Examination Survey Data

One common age-related health problem is the loss of bone mineral density (BMD), which can lead to a variety of negative health outcomes, including increased risk of spinal fracture. In this study, the authors investigate risk factors that may be predictive of an individual's risk of spinal fracture. Their findings provide valuable information that clinicians can use in patient evaluations.

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A Novel Method for Assessment of Proprioception

Trevithick et al. | Jun 22, 2018

A Novel Method for Assessment of Proprioception

Trevithick & Park were interested in whether proprioception, the sense of the relative position of body parts and movement, differed between varsity and non-varsity athletes, as well as between the sport practiced. The authors found that there was no correlation between athleticism and better proprioception, but that dancers had superior proprioceptive abilities compared to those that practiced other sports.

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Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

Ramprasad et al. | Mar 18, 2020

Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

In this study, the authors test whether providing a larger dataset of glass transition temperatures (Tg) to train the machine-learning platform Polymer Genome would improve its accuracy. Polymer Genome is a machine learning based data-driven informatics platform for polymer property prediction and Tg is one property needed to design new polymers in silico. They found that training the model with their larger, curated dataset improved the algorithm's Tg, providing valuable improvements to this useful platform.

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