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Occupational Exposure

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Potential of deep learning in assessing pneumoconiosis depicted on digital chest radiography.

Occupational and environmental medicine
OBJECTIVES: To investigate the potential of deep learning in assessing pneumoconiosis depicted on digital chest radiographs and to compare its performance with certified radiologists.

Concerns for management of STEMI patients in the COVID-19 era: a paradox phenomenon.

Journal of thrombosis and thrombolysis
The pandemic of coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. During this time, the management of people with acute coronary syndromes (ACS) and COVID-19 has become a global issue, especially since...

Development of rapid and highly accurate method to measure concentration of fibers in atmosphere using artificial intelligence and scanning electron microscopy.

Journal of occupational health
AIM: We aimed to develop a measurement method that can count fibers rapidly by scanning electron microscopy equipped with an artificial intelligence image recognition system (AI-SEM), detecting thin fibers which cannot be observed by a conventional p...

Prediction of impacts on liver enzymes from the exposure of low-dose medical radiations through artificial intelligence algorithms.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVES: This study aimed to develop artificial intelligence and machine learning-based models to predict alterations in liver enzymes from the exposure of low annual average effective doses in radiology and nuclear medicine personnel of Institute...

Evaluation of external contamination on the vial surfaces of some hazardous drugs that commonly used in Chinese hospitals and comparison between environmental contamination generated during robotic compounding by IV: Dispensing robot vs. manual compounding in biological safety cabinet.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
OBJECTIVES: The aims of the study were to evaluate the external contamination of hazardous drug vials used in Chinese hospitals and to compare environmental contamination generated by a robotic intelligent dispensing system (WEINAS) and a manual comp...

Radiation Protection and Occupational Exposure on Ga-PSMA-11-Based Cerenkov Luminescence Imaging Procedures in Robot-Assisted Prostatectomy.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Cerenkov luminescence imaging (CLI) was successfully implemented in the intraoperative context as a form of radioguided cancer surgery, showing promise in the detection of surgical margins during robot-assisted radical prostatectomy. The present stud...

Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects.

International journal of environmental research and public health
OBJECTIVE: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos.

Rapid Robot-Aided On-site Testing of Fume Cupboards.

Annals of work exposures and health
Although containment testing of fume cupboards (FC) according to the standards EN 14175-3 (2019) or ANSI/ASHRAE 110 (2016) is well established for type testing, its application is currently much less accepted and practised for evaluating containment ...

Evaluation of cancer drug infusion devices prior to the implementation of a compounding robot.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
INTRODUCTION: Compounding robots are increasingly being implemented in hospital pharmacies. In our hospital, the recent acquisition of a robot (RIVA, ARxIUM) for intravenous cancer drug compounding obliged us to replace the previously used infusion d...

Deep learning for asbestos counting.

Journal of hazardous materials
The PCM (phase contrast microscopy) method for asbestos counting needs special sample treatments, hence it is time consuming and rather expensive. As an alternative, we implemented a deep learning procedure on images directly acquired from the untrea...