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Penetration and familiarity of false belief on neuroscience among students and its modifiability

Takeshi Hatta, Taketoshi Hatta, Kazuhisa Todayama, Minoru Karasawa • Journal of Human Environmental Studies (2010)

In Study 1, the degrees of penetration and familiarity of false belief on neuroscience, especially brain imaging, among students were surveyed using a questionnaire technique. A total number of 485 students from medical school, school of nu...

DOAJ Open Access (DOAJ) DOI: 10.4189/shes.8.155

Impact of a Mobile App (LoAD Calc) on the Calculation of Maximum Safe Doses of Local Anesthetics: Protocol for a Randomized Controlled Trial

Pietro Elias Fubini, Georges Louis Savoldelli, Tal Sara Beckmann, Caroline Flora Samer et al. • JMIR Research Protocols (2024)

BackgroundLocal anesthetics (LAs) are regularly used to alleviate pain during medical or surgical procedures. Their use is generally considered safe, but exceeding the maximum recommended doses can lead to LA systemic toxicity, a rare but p...

DOAJ Open Access (DOAJ) DOI: 10.2196/53679

Early Retinal Microvascular Alterations in Young Type 1 Diabetic Patients without Clinical Retinopathy

Alexandra Oltea Dan, Alin Ștefănescu-Dima, Andrei Teodor Bălășoiu, Ileana Puiu et al. • Diagnostics (2023)

The purpose of this study is to identify and quantify preclinical changes with the help of optical coherence tomography angiography (OCTA) within the retinal microcirculation of young type 1 diabetes (T1D) patients without clinical signs of...

DOAJ Open Access (DOAJ) DOI: 10.3390/diagnostics13091648

Exploring feature selection and classification methods for predicting heart disease

Robinson Spencer, Fadi Thabtah, Neda Abdelhamid, Michael Thompson • Digital Health (2020)

Machine learning has been used successfully to improve the accuracy of computer-aided diagnosis systems. This paper experimentally assesses the performance of models derived by machine learning techniques by using relevant features chosen b...

DOAJ Open Access (DOAJ) DOI: 10.1177/2055207620914777

Dataset on Women's empowerment, land and donor-driven agricultural interventions in Eastern Zambia

Progress H. Nyanga, Bridget Bwalya Umar, Douty Chibamba, Wilma S. Nchito • Data in Brief (2020)

A survey was conducted with 235 randomly selected households to investigate women's empowerment, land and donor-driven agricultural interventions in Eastern Zambia [1] for aid programmes with (Norwegian) and without (Chinese) women empowerm...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2020.106113

From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive Disorder

Chunyu Pan, Ying Ma, Lifei Wang, Yan Zhang et al. • Brain Sciences (2024)

Major Depressive Disorder (MDD) is a significant neurological condition associated with aberrations in brain functional networks. Traditional studies have predominantly analyzed these from a network topology perspective. However, given the ...

DOAJ Open Access (DOAJ) DOI: 10.3390/brainsci14050509

A genome-wide association study on meat consumption in a Japanese population: the Japan Multi-Institutional Collaborative Cohort study

Yasuyuki Nakamura, Akira Narita, Yoichi Sutoh, Nahomi Imaeda et al. • Journal of Nutritional Science (2021)

Recent genome-wide association studies (GWAS) on the dietary habits of the Japanese population have shown that an effect rs671 allele was inversely associated with fish consumption, whereas it was directly associated with coffee consumption...

DOAJ Open Access (DOAJ) DOI: 10.1017/jns.2021.49

Accelerated maximum likelihood parameter estimation for stochastic biochemical systems

Daigle Bernie J, Roh Min K, Petzold Linda R, Niemi Jarad • BMC Bioinformatics (2012)

Abstract Background A prerequisite for the mechanistic simulation of a biochemical system is detailed knowledge of its kinetic parameters. Despite recent experimental advances, the estimation of unknown parameter values from observed data i...

DOAJ Open Access (DOAJ) DOI: 10.1186/1471-2105-13-68

Integrating machine learning algorithms and explainable artificial intelligence approach for predicting patient unpunctuality in psychiatric clinics

Alireza Kasaie, Suchithra Rajendran • Healthcare Analytics (2023)

This study addresses patient unpunctuality, a major concern affecting patient waiting time, resource utilization, and quality of care. We develop and compare four machine learning models, including multinomial logistic regression, decision ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.health.2023.100242

Patients’ needs and experiences of telerehabilitation after total hip and knee arthroplasty: A qualitative systematic review and meta-synthesis

Wenzhong Zhang, Hong Ji, Yan Wu, Zhenzhen Xu et al. • Digital Health (2024)

Background The number of patients undergoing joint replacement procedures is continuously increasing. Tele-equipment is progressively being employed for postrehabilitation of total hip and knee replacements. Gaining a comprehensive understa...

DOAJ Open Access (DOAJ) DOI: 10.1177/20552076241256756

Functional neuroimaging of visuospatial working memory tasks enables accurate detection of attention deficit and hyperactivity disorder

Rubi Hammer, Gillian E. Cooke, Mark A. Stein, James R. Booth • NeuroImage: Clinical (2015)

Finding neurobiological markers for neurodevelopmental disorders, such as attention deficit and hyperactivity disorder (ADHD), is a major objective of clinicians and neuroscientists. We examined if functional Magnetic Resonance Imaging (fMR...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.nicl.2015.08.015

The role of medical informatics in the management of medical information

Jun Hirose, Yoshifumi Wakata, Masato Tagi, Yu Tamaki • The Journal of Medical Investigation (2020)

With progress in information and communication technology, medical information has been converted to digital formats and stored and managed using computer systems. The construction, management, and operation of medical information systems a...

OPENALEX Open Access DOI: https://doi.org/10.2152/jmi.67.27