Elgendi Mohamed
Department of Obstetrics & Gynecology, University of British Columbia and BC Children's & Women's Hospital, Vancouver, BC V6H 3N1, Canada.
School of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Diseases. 2018 Jan 6;6(1):6. doi: 10.3390/diseases6010006.
Algorithm development in digital medicine necessitates ongoing knowledge and skills updating to match the current demands and constant progression in the field. In today's chaotic world there is an increasing trend to seek out simple solutions for complex problems that can increase efficiency, reduce resource consumption, and improve scalability. This desire has spilled over into the world of science and research where many disciplines have taken to investigating and applying more simplistic approaches. Interestingly, through a review of current literature and research efforts, it seems that the learning and teaching principles in digital medicine continue to push towards the development of sophisticated algorithms with a limited scope and has not fully embraced or encouraged a shift towards more simple solutions that yield equal or better results. This short note aims to demonstrate that within the world of digital medicine and engineering, simpler algorithms can offer effective and efficient solutions, where traditionally more complex algorithms have been used. Moreover, the note demonstrates that bridging different research disciplines is very beneficial and yields valuable insights and results.
数字医学中的算法开发需要持续更新知识和技能，以适应该领域当前的需求和不断发展。在当今这个纷繁复杂的世界里，人们越来越倾向于为复杂问题寻找简单的解决方案，这些方案可以提高效率、减少资源消耗并增强可扩展性。这种需求已经蔓延到科学研究领域，许多学科都在探索和应用更简化的方法。有趣的是，通过回顾当前的文献和研究成果，数字医学中的学习和教学原则似乎仍在推动开发范围有限的复杂算法，尚未充分接受或鼓励转向能产生同等或更好效果的更简单解决方案。本短文旨在表明，在数字医学和工程领域，传统上使用更复杂算法的地方，更简单的算法也能提供有效且高效的解决方案。此外，该短文还表明，跨不同研究学科进行融合非常有益，能产生有价值的见解和成果。
