Many training programs have been designed using modern software to restore the impaired cognitive functions in patients with acquired brain damage (ABD). The objective of this study was to evaluate the effectiveness of a computer-based training program of attention and memory in patients with ABD, using a two-armed parallel group design, where the experimental group ( = 50) received cognitive stimulation using RehaCom software, and the control group ( = 30) received the standard cognitive stimulation (non-computerized) for eight weeks. In order to assess the possible cognitive changes after the treatment, a post-pre experimental design was employed using the following neuropsychological tests: Wechsler Memory Scale (WMS) and Trail Making test A and B. The effectiveness of the training procedure was statistically significant ( < 0.05) when it established the comparison between the performance in these scales, before and after the training period, in each patient and between the two groups. The training group had statistically significant ( < 0.001) changes in focused attention (Trail A), two subtests (digit span and logical memory), and the overall score of WMS. Finally, we discuss the advantages of computerized training rehabilitation and further directions of this line of work.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5791022 | PMC |
http://dx.doi.org/10.3390/bs8010004 | DOI Listing |
Diagnostics (Basel)
December 2024
Department of Computer Science, Tunghai University, Taichung 407224, Taiwan.
Background And Objective: Cardiovascular disease (CVD), one of the chronic non-communicable diseases (NCDs), is defined as a cardiac and vascular disorder that includes coronary heart disease, heart failure, peripheral arterial disease, cerebrovascular disease (stroke), congenital heart disease, rheumatic heart disease, and elevated blood pressure (hypertension). Having CVD increases the mortality rate. Emotional stress, an indirect indicator associated with CVD, can often manifest through facial expressions.
View Article and Find Full Text PDFJ Family Med Prim Care
December 2024
Founder and Chairman Emeritus, Academy of Family Physicians of India, New Delhi, India.
The National Eligibility cum Entrance Test for Undergraduate (NEET-UG) in India serves as a unified admission examination for undergraduate medical courses, aiming to standardize assessment across diverse educational backgrounds. Despite its goals, NEET-UG has faced criticism over fairness, excessive reliance on coaching, and its impact on students' holistic development. The article reviews the limitations of the current NEET-UG format and proposes reforms, emphasizing the need to align the syllabus more closely with medical requirements by reducing physics and chemistry content and prioritizing biology.
View Article and Find Full Text PDFRadiography (Lond)
January 2025
UniSA Allied Health & Human Performance, University of South Australia, Adelaide, SA 5001, Australia.
Introduction: Radiographers support the multidisciplinary team by facilitating medical imaging within the operating theatre environment. This project aimed to enhance student readiness for clinical competency in operative theatre imaging by implementing an authentic C-arm simulator for students to use prior to attending clinical placement.
Methods: This study followed a pre-post, quantitative study design.
BMJ Support Palliat Care
January 2025
Tianjin University of Traditional Chinese Medicine, Tianjin, China
Purpose: To assess the prevalence of preoperative frailty in patients with oesophageal cancer and its impact on postoperative outcomes and overall survival.
Methods: A comprehensive computer-based search of the CNKI, Wanfang, VIP, CBM, PubMed, Embase, Cochrane Library, Web of Science and CINAHL databases was conducted for articles related to preoperative frailty in patients with oesophageal cancer. The search was carried out from the time of the construction of the database to 20 April 2024.
Biomedicine (Taipei)
December 2024
School of Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan.
Introduction: Our previous research demonstrated that a large language model (LLM) based on the transformer architecture, specifically the MegaMolBART encoder with an XGBoost classifier, effectively predicts the blood-brain barrier (BBB) permeability of compounds. However, the permeability coefficients of compounds that can traverse this barrier remain unclear. Additionally, the absorption, distribution, metabolism, and excretion (ADME) characteristics of substances obtained from the Natural Product Research Laboratory (NPRL) at China Medical University Hospital (CMUH) have not yet been determined.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!