Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
The purpose of this study it to assess the effect of sequential learning of self-training support vector machine (ST-S3VM) on short- and long-term surface electromyogram (sEMG) datasets. A machine learning-based supervised classi-fier is enabling sta...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Advancements in deep learning techniques have proved useful in biomedical image segmentation. However, the large amount of unlabeled data inherent in biomedical imagery, particularly in digital pathology, creates a semi-supervised learning paradigm. ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Image segmentation models trained only with image-level labels have become increasingly popular as they require significantly less annotation effort than models trained with scribble, bounding box or pixel-wise annotations. While methods utilizing im...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Biomedical text classification requires having training examples labeled by clinical specialists, a process that can be costly. To address this problem, active learning incrementally selects a subset of the most informative unlabeled examples, sample...
Studies in health technology and informatics
Jun 6, 2022
Self-supervised methods gain more and more attention, especially in the medical domain, where the number of labeled data is limited. They provide results on par or superior to their fully supervised competitors, yet the difference between information...
BMJ health & care informatics
Apr 1, 2022
OBJECTIVES: The Indian Liver Patient Dataset (ILPD) is used extensively to create algorithms that predict liver disease. Given the existing research describing demographic inequities in liver disease diagnosis and management, these algorithms require...
Briefings in bioinformatics
Mar 10, 2022
With the rapid growth of high-resolution microscopy imaging data, revealing the subcellular map of human proteins has become a central task in the spatial proteome. The cell atlas of the Human Protein Atlas (HPA) provides precious resources for recog...
Studies in health technology and informatics
Jan 14, 2022
Zoning classification is a rating mechanism, which uses a three-tier color coding to indicate perceived risk from the patients' conditions. It is a widely adopted manual system used across mental health settings, however it is time consuming and cost...
Studies in health technology and informatics
Jan 14, 2022
The goal of this study was to build a machine learning model for early prostate cancer prediction based on healthcare utilization patterns. We examined the frequency and pattern changes of healthcare utilization in 2916 prostate cancer patients 3 yea...
American journal of clinical pathology
Jan 6, 2022
OBJECTIVES: Developing accurate supervised machine learning algorithms is hampered by the lack of representative annotated datasets. Most data in anatomic pathology are unlabeled and creating large, annotated datasets is a time consuming and laboriou...