期刊
JOURNAL OF PERSONALIZED MEDICINE
卷 12, 期 3, 页码 -出版社
MDPI
DOI: 10.3390/jpm12030480
关键词
computer-aided decision; learning models; CT scan; lung cancer
资金
- National Funds through the Portuguese funding agency, FCT-Foundation for Science and Technology Portugal [LA/P/0063/2020, 2021.05767.BD]
- Fundação para a Ciência e a Tecnologia [2021.05767.BD] Funding Source: FCT
Advancements in computer-aided decision systems have brought significant benefits to healthcare, particularly in the field of lung cancer where accurate clinical procedures are crucial. This review focuses on the development of CAD tools using computed tomography images for lung cancer-related tasks and discusses current challenges and future directions in integrating artificial intelligence in healthcare.
Advancements in the development of computer-aided decision (CAD) systems for clinical routines provide unquestionable benefits in connecting human medical expertise with machine intelligence, to achieve better quality healthcare. Considering the large number of incidences and mortality numbers associated with lung cancer, there is a need for the most accurate clinical procedures; thus, the possibility of using artificial intelligence (AI) tools for decision support is becoming a closer reality. At any stage of the lung cancer clinical pathway, specific obstacles are identified and motivate the application of innovative AI solutions. This work provides a comprehensive review of the most recent research dedicated toward the development of CAD tools using computed tomography images for lung cancer-related tasks. We discuss the major challenges and provide critical perspectives on future directions. Although we focus on lung cancer in this review, we also provide a more clear definition of the path used to integrate AI in healthcare, emphasizing fundamental research points that are crucial for overcoming current barriers.
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