AIMC Topic: Humans

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Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net.

Medical image analysis
The identification and quantification of liver lesions changes in longitudinal contrast enhanced CT (CECT) scans is required to evaluate disease status and to determine treatment efficacy in support of clinical decision-making. This paper describes a...

Researcher reasoning meets computational capacity: Machine learning for social science.

Social science research
Computational power and big data have created new opportunities to explore and understand the social world. A special synergy is possible when social scientists combine human attention to certain aspects of the problem with the power of algorithms to...

Addressing the Challenges and Barriers to the Integration of Machine Learning into Clinical Practice: An Innovative Method to Hybrid Human-Machine Intelligence.

Sensors (Basel, Switzerland)
Machine learning (ML) models have proven their potential in acquiring and analyzing large amounts of data to help solve real-world, complex problems. Their use in healthcare is expected to help physicians make diagnoses, prognoses, treatment decision...

What Is a Digital Twin? Experimental Design for a Data-Centric Machine Learning Perspective in Health.

International journal of molecular sciences
The idea of a digital twin has recently gained widespread attention. While, so far, it has been used predominantly for problems in engineering and manufacturing, it is believed that a digital twin also holds great promise for applications in medicine...

Classifier for the functional state of the respiratory system via descriptors determined by using multimodal technology.

Computer methods in biomechanics and biomedical engineering
Currently, intelligent systems built on a multimodal basis are used to study the functional state of living objects. Its essence lies in the fact that a decision is made through several independent information channels with the subsequent aggregation...

Long-term comparative outcome analysis of a robot-assisted laparoscopic prostatectomy with retropubic radical prostatectomy by a single surgeon.

Journal of robotic surgery
We aimed to report a comprehensive outcome analysis of robot-assisted laparoscopic prostatectomies (RALP) performed by a single surgeon and compared it to retropubic radical prostatectomies (RRP) done by the same surgeon in a high-volume center. Preo...

Artificial intelligence using deep learning to predict the anatomical outcome of rhegmatogenous retinal detachment surgery: a pilot study.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To develop and evaluate an automated deep learning model to predict the anatomical outcome of rhegmatogenous retinal detachment (RRD) surgery.

Trends in clinical validation and usage of US Food and Drug Administration-cleared artificial intelligence algorithms for medical imaging.

Clinical radiology
AIM: To examine the current landscape of US Food and Drug Administration (FDA)-approved artificial intelligence (AI) medical imaging devices and identify trends in clinical validation strategy.

Simplified approach to the medial internal iliac region using a uretero-hypogastric nerve fascia development procedure for extended pelvic lymph node dissection during robot-assisted radical prostatectomy for high-risk prostate cancer.

International journal of urology : official journal of the Japanese Urological Association
INTRODUCTION: Although several clinical guidelines for prostate cancer (PC) recommend extended pelvic lymph node dissection (ePLND) during radical prostatectomy for high-risk cases, there are several issues to consider, including certain technical as...