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Advanced Technology in a Real-World Rehabilitation Setting: Longitudinal Observational Study on Clinician Adoption and Implementation.
J Med Internet Res
December 2024
Institute for Musculoskeletal Health, Sydney Local Health District, Sydney, Australia.
Background: Advanced technologies are becoming increasingly accessible in rehabilitation. Current research suggests technology can increase therapy dosage, provide multisensory feedback, and reduce manual handling for clinicians. While more high-quality evidence regarding the effectiveness of rehabilitation technologies is needed, understanding of how to effectively integrate technology into clinical practice is also limited.
View Article and Find Full Text PDFNAC4ED: A high-throughput computational platform for the rational design of enzyme activity and substrate selectivity.
mLife
December 2024
Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development School of Chemistry and Molecular Engineering, East China Normal University Shanghai China.
In silico computational methods have been widely utilized to study enzyme catalytic mechanisms and design enzyme performance, including molecular docking, molecular dynamics, quantum mechanics, and multiscale QM/MM approaches. However, the manual operation associated with these methods poses challenges for simulating enzymes and enzyme variants in a high-throughput manner. We developed the NAC4ED, a high-throughput enzyme mutagenesis computational platform based on the "near-attack conformation" design strategy for enzyme catalysis substrates.
View Article and Find Full Text PDFVAE-IF: Deep feature extraction with averaging for fully unsupervised artifact detection in routinely acquired ICU time-series.
Comput Biol Med
December 2024
Institute for Imaging, Data and Communications (IDCOM), School of Engineering, University of Edinburgh, Edinburgh, EH9 3FB, UK.
Artifacts are a common problem in physiological time series collected from intensive care units (ICU) and other settings. They affect the quality and reliability of clinical research and patient care. Manual annotation of artifacts is costly and time-consuming, rendering it impractical.
View Article and Find Full Text PDFLearnable color space conversion and fusion for stain normalization in pathology images.
Med Image Anal
December 2024
School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China; Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China; Shanghai Clinical Research and Trial Center, Shanghai, China. Electronic address:
Variations in hue and contrast are common in H&E-stained pathology images due to differences in slide preparation across various institutions. Such stain variations, while not affecting pathologists much in diagnosing the biopsy, pose significant challenges for computer-assisted diagnostic systems, leading to potential underdiagnosis or misdiagnosis, especially when stain differentiation introduces substantial heterogeneity across datasets from different sources. Traditional stain normalization methods, aimed at mitigating these issues, often require labor-intensive selection of appropriate templates, limiting their practicality and automation.
View Article and Find Full Text PDFCsec-net: a novel deep features fusion and entropy-controlled firefly feature selection framework for leukemia classification.
Health Inf Sci Syst
December 2025
Department of Electrical Engineering, Iqra National University, Peshawar, 25000 Pakistan.
Leukemia, a life-threatening form of cancer, poses a significant global health challenge affecting individuals of all age groups, including both children and adults. Currently, the diagnostic process relies on manual analysis of microscopic images of blood samples. In recent years, machine learning employing deep learning approaches has emerged as cutting-edge solutions for image classification problems.
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