
arXiv: 2203.01643
There is a growing need to assist radiologists in performing X-ray readings and diagnoses fast, comfortably, and effectively. As radiologists strive to maximize productivity, it is essential to consider the impact of reading rooms in interpreting complex examinations and ensure that higher volume and reporting speeds do not compromise patient outcomes. Virtual Reality (VR) is a disruptive technology for clinical practice in assessing X-ray images. We argue that conjugating eye-tracking with VR devices and Machine Learning may overcome obstacles posed by inadequate ergonomic postures and poor room conditions that often cause erroneous diagnostics when professionals examine digital images.
FOS: Computer and information sciences, Computer Science - Machine Learning, 616, Applied Computing-Life and medical Sciences-Health informatics Computing methodologies-Artificial intelligence-Knowledge representation and reasoning-Causal rea-soning and diagnostics Human-centered computing-Virtual reality, Computer Science - Human-Computer Interaction, 600, Human-Computer Interaction (cs.HC), Machine Learning (cs.LG)
FOS: Computer and information sciences, Computer Science - Machine Learning, 616, Applied Computing-Life and medical Sciences-Health informatics Computing methodologies-Artificial intelligence-Knowledge representation and reasoning-Causal rea-soning and diagnostics Human-centered computing-Virtual reality, Computer Science - Human-Computer Interaction, 600, Human-Computer Interaction (cs.HC), Machine Learning (cs.LG)
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