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一种基于人工智能的癌症患者数据分析与预后评估工具:Clarify研究结果

An Artificial Intelligence-Based Tool for Data Analysis and Prognosis in Cancer Patients: Results from the Clarify Study.

作者信息

Torrente María, Sousa Pedro A, Hernández Roberto, Blanco Mariola, Calvo Virginia, Collazo Ana, Guerreiro Gracinda R, Núñez Beatriz, Pimentao Joao, Sánchez Juan Cristóbal, Campos Manuel, Costabello Luca, Novacek Vit, Menasalvas Ernestina, Vidal María Esther, Provencio Mariano

机构信息

Department of Medical Oncology, Puerta de Hierro-Majadahonda University Hospital, 28222 Madrid, Spain.

Faculty of Health Sciences, Francisco de Vitoria University, 28223 Madrid, Spain.

出版信息

Cancers (Basel). 2022 Aug 22;14(16):4041. doi: 10.3390/cancers14164041.

Abstract

BACKGROUND

Artificial intelligence (AI) has contributed substantially in recent years to the resolution of different biomedical problems, including cancer. However, AI tools with significant and widespread impact in oncology remain scarce. The goal of this study is to present an AI-based solution tool for cancer patients data analysis that assists clinicians in identifying the clinical factors associated with poor prognosis, relapse and survival, and to develop a prognostic model that stratifies patients by risk.

MATERIALS AND METHODS

We used clinical data from 5275 patients diagnosed with non-small cell lung cancer, breast cancer, and non-Hodgkin lymphoma at Hospital Universitario Puerta de Hierro-Majadahonda. Accessible clinical parameters measured with a wearable device and quality of life questionnaires data were also collected.

RESULTS

Using an AI-tool, data from 5275 cancer patients were analyzed, integrating clinical data, questionnaires data, and data collected from wearable devices. Descriptive analyses were performed in order to explore the patients' characteristics, survival probabilities were calculated, and a prognostic model identified low and high-risk profile patients.

CONCLUSION

Overall, the reconstruction of the population's risk profile for the cancer-specific predictive model was achieved and proved useful in clinical practice using artificial intelligence. It has potential application in clinical settings to improve risk stratification, early detection, and surveillance management of cancer patients.

摘要

背景

近年来,人工智能(AI)在解决包括癌症在内的各种生物医学问题方面做出了重大贡献。然而,在肿瘤学领域具有重大且广泛影响的人工智能工具仍然稀缺。本研究的目的是提出一种基于人工智能的癌症患者数据分析解决方案工具,以协助临床医生识别与预后不良、复发和生存相关的临床因素,并开发一种根据风险对患者进行分层的预后模型。

材料与方法

我们使用了来自普埃尔塔德耶罗 - 马亚达洪达大学医院5275例被诊断为非小细胞肺癌、乳腺癌和非霍奇金淋巴瘤患者的临床数据。还收集了通过可穿戴设备测量的可获取临床参数以及生活质量问卷数据。

结果

使用人工智能工具对5275例癌症患者的数据进行了分析,整合了临床数据、问卷数据和从可穿戴设备收集的数据。进行了描述性分析以探索患者特征,计算了生存概率,并确定了一个预后模型来识别低风险和高风险特征的患者。

结论

总体而言,实现了针对癌症特异性预测模型的人群风险特征重建,并证明在使用人工智能的临床实践中是有用的。它在临床环境中具有潜在应用价值,可改善癌症患者的风险分层、早期检测和监测管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5454/9406336/223850cc91af/cancers-14-04041-g001.jpg

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