AIMC Topic: Humans

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Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Machine learning on electromyography (EMG) has recently achieved remarkable success on various tasks, while such success relies heavily on the assumption that the training and future data must be of the same data distribution. However, this assumptio...

Data-driven decisions about individual patients: The case of medical AI.

Journal of evaluation in clinical practice
There are high hopes that clinical decisions can be improved by adopting algorithms trained to estimate the likelihood that a patient suffers a condition C. Introducing work on the epistemic value of purely statistical evidence in legal epistemology ...

Shortening Acquisition Time and Improving Image Quality for Pelvic MRI Using Deep Learning Reconstruction for Diffusion-Weighted Imaging at 1.5 T.

Academic radiology
RATIONALE AND OBJECTIVES: To determine the impact on acquisition time reduction and image quality of a deep learning (DL) reconstruction for accelerated diffusion-weighted imaging (DWI) of the pelvis at 1.5 T compared to standard DWI.

Artificial Intelligence and Pathomics: Prostate Cancer.

The Urologic clinics of North America
Artificial intelligence (AI) has the potential to transform pathologic diagnosis and cancer patient management as a predictive and prognostic biomarker. AI-based systems can be used to examine digitally scanned histopathology slides and differentiate...

Developing a model to explain users' ethical perceptions regarding the use of care robots in home care: A cross-sectional study in Ireland, Finland, and Japan.

Archives of gerontology and geriatrics
To date, research on ethical issues regarding care robots for older adults, family caregivers, and care workers has not progressed sufficiently. This study aimed to build a model that universally explains the relationship between the use of care robo...

ExpHBA Deep-IoT: Exponential Honey Badger Optimized Deep Learning For Breast Cancer Detection in IoT Healthcare System.

Journal of digital imaging
Breast cancer (BC) is the most widely found disease among women in the world. The early detection of BC can frequently lessen the mortality rate as well as progress the probability of providing proper treatment. Hence, this paper focuses on devising ...

Artificial intelligence (A.I.) in dental curricula: Ethics and responsible integration.

Journal of dental education
The use of artificial intelligence (AI) is deeply embedded in all aspects of our daily lives, promoting efficiency and safety in routine tasks at home and work. Likewise, dentistry is rapidly exploring new uses of AI for image analysis, electronic he...

A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

Progress in biophysics and molecular biology
The risk of discovering an intracranial aneurysm during the initial screening and follow-up screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these mass effects, unruptured aneurysms frequently generate symptoms, how...

Lymph node dissection during radical cystectomy for bladder cancer: A two-center comparative study of robotic versus open surgery.

Asian journal of endoscopic surgery
INTRODUCTION: This study was performed to evaluate the safety and efficacy of lymph node dissection (LND) during robot-assisted radical cystectomy (RARC) compared with open radical cystectomy (ORC).