皮肤癌是全球最常见的形式之一,在过去的几十年中,发病率显着增加。早期和准确检测这种类型的癌症可以导致更好的预后和对患者的侵入性治疗。随着人工智能(AI)的进步,工具已经出现,可以促进诊断和分类皮肤病学图像,补充传统的临床评估,并适用于缺乏专家的情况。它的采用需要对功效进行分析,安全,和道德考虑,以及考虑患者的遗传和种族多样性。
■系统综述旨在检查有关检测的研究,分类,以及临床环境中皮肤癌图像的评估。
■我们对PubMed进行了系统的文献检索,Scopus,Embase,和WebofScience,包括直到4月4日发表的研究,2023年。研究选择,数据提取,和批判性评估是由两名独立的审查员进行的。结果随后通过叙述性综合呈现。
■通过搜索,在四个数据库中确定了760项研究,其中只有18项研究被选中,注重发展,实施,并验证系统以检测,诊断,并在临床环境中对皮肤癌进行分类。这篇综述涵盖了描述性分析,数据场景,数据处理和技术,研究结果和观点,和医生的多样性,可访问性,和参与。
■人工智能在皮肤病学中的应用有可能彻底改变皮肤癌的早期检测。然而,必须验证并与医疗保健专业人员合作,以确保其临床有效性和安全性。
UNASSIGNED: Skin cancer is one of the most common forms worldwide, with a significant increase in incidence over the last few decades. Early and accurate detection of this type of cancer can result in better prognoses and less invasive treatments for patients. With advances in Artificial Intelligence (AI), tools have emerged that can facilitate diagnosis and classify dermatological images, complementing traditional clinical assessments and being applicable where there is a shortage of specialists. Its adoption requires analysis of efficacy, safety, and ethical considerations, as well as considering the genetic and ethnic diversity of patients.
UNASSIGNED: The systematic
review aims to examine research on the detection, classification, and assessment of skin cancer images in clinical settings.
UNASSIGNED: We conducted a systematic literature search on PubMed, Scopus, Embase, and Web of Science, encompassing studies published until April 4th, 2023. Study selection, data extraction, and critical appraisal were carried out by two independent reviewers. Results were subsequently presented through a narrative synthesis.
UNASSIGNED: Through the search, 760 studies were identified in four databases, from which only 18 studies were selected, focusing on developing, implementing, and validating systems to detect, diagnose, and classify skin cancer in clinical settings. This
review covers descriptive analysis, data scenarios, data processing and techniques, study results and perspectives, and physician diversity, accessibility, and participation.
UNASSIGNED: The application of artificial intelligence in dermatology has the potential to revolutionize early detection of skin cancer. However, it is imperative to validate and collaborate with healthcare professionals to ensure its clinical effectiveness and safety.