AIMC Topic: Humans

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Deep learning-based automatic bleeding recognition during liver resection in laparoscopic hepatectomy.

Surgical endoscopy
BACKGROUND: Intraoperative hemorrhage during laparoscopic hepatectomy (LH) is a risk factor for negative postoperative outcomes. Ensuring appropriate hemostasis enhances the safety of surgical procedures. An automatic bleeding recognition system base...

Artificial intelligence: a primer for pediatric radiologists.

Pediatric radiology
Artificial intelligence (AI) is increasingly recognized for its transformative potential in radiology; yet, its application in pediatric radiology is relatively limited when compared to the whole of radiology. This manuscript introduces pediatric rad...

Application and Prospects of Deep Learning Technology in Fracture Diagnosis.

Current medical science
Artificial intelligence (AI) is an interdisciplinary field that combines computer technology, mathematics, and several other fields. Recently, with the rapid development of machine learning (ML) and deep learning (DL), significant progress has been m...

Prediction and Elimination of Physiological Tremor During Control of Teleoperated Robot Based on Deep Learning.

Sensors (Basel, Switzerland)
Currently, teleoperated robots, with the operator's input, can fully perceive unknown factors in a complex environment and have strong environmental interaction and perception abilities. However, physiological tremors in the human hand can seriously ...

Toward Improving Human Training by Combining Wearable Full-Body IoT Sensors and Machine Learning.

Sensors (Basel, Switzerland)
This paper proposes DigitalUpSkilling, a novel IoT- and AI-based framework for improving and personalising the training of workers who are involved in physical-labour-intensive jobs. DigitalUpSkilling uses wearable IoT sensors to observe how individu...

Convergence of Nanotechnology and Machine Learning: The State of the Art, Challenges, and Perspectives.

International journal of molecular sciences
Nanotechnology and machine learning (ML) are rapidly emerging fields with numerous real-world applications in medicine, materials science, computer engineering, and data processing. ML enhances nanotechnology by facilitating the processing of dataset...

vScreenML v2.0: Improved Machine Learning Classification for Reducing False Positives in Structure-Based Virtual Screening.

International journal of molecular sciences
The enthusiastic adoption of make-on-demand chemical libraries for virtual screening has highlighted the need for methods that deliver improved hit-finding discovery rates. Traditional virtual screening methods are often inaccurate, with most compoun...

Evolving and Novel Applications of Artificial Intelligence in Abdominal Imaging.

Tomography (Ann Arbor, Mich.)
Advancements in artificial intelligence (AI) have significantly transformed the field of abdominal radiology, leading to an improvement in diagnostic and disease management capabilities. This narrative review seeks to evaluate the current standing of...

Analysis of public perceptions on the use of artificial intelligence in genomic medicine.

Human genomics
PURPOSE: Next generation sequencing has led to the creation of large pools of genomic data with analysis rather than data generation now the limiting factor. Artificial intelligence (AI) may be required to optimize the benefits of these data, but lit...

Forecasting the future of smart hospitals: findings from a real-time delphi study.

BMC health services research
BACKGROUND: In concert with other digital technologies, artificial intelligence (AI) is shaping the vision of smart hospitals. The transformation into smart hospitals, however, is all but trivial due to the lack of financial and human resources, digi...