Translation of AI into oncology clinical practice
Artificial intelligence (AI) is a transformative technology that is capturing popular imagination
and can revolutionize biomedicine. AI and machine learning (ML) algorithms have the …
and can revolutionize biomedicine. AI and machine learning (ML) algorithms have the …
Machine learning for lung cancer diagnosis, treatment, and prognosis
The recent development of imaging and sequencing technologies enables systematic
advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in …
advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in …
Developing artificial intelligence models for extracting oncologic outcomes from japanese electronic health records
K Araki, N Matsumoto, K Togo, N Yonemoto, E Ohki… - Advances in …, 2023 - Springer
Introduction A framework that extracts oncological outcomes from large-scale databases
using artificial intelligence (AI) is not well established. Thus, we aimed to develop AI models …
using artificial intelligence (AI) is not well established. Thus, we aimed to develop AI models …
Random forest classifier improving phenylketonuria screening performance in two Chinese populations
Y Song, Z Yin, C Zhang, S Hao, H Li, S Wang… - Frontiers in Molecular …, 2022 - frontiersin.org
Phenylketonuria (PKU) is a genetic disorder with amino acid metabolic defect, which does
great harms to the development of newborns and children. Early diagnosis and treatment …
great harms to the development of newborns and children. Early diagnosis and treatment …
Profile of the multicenter cohort of the German Cancer Consortium's Clinical Communication Platform
D Maier, JJ Vehreschild, B Uhl, S Meyer… - European Journal of …, 2023 - Springer
Abstract Treatment concepts in oncology are becoming increasingly personalized and
diverse. Successively, changes in standards of care mandate continuous monitoring of …
diverse. Successively, changes in standards of care mandate continuous monitoring of …
[引用][C] Developing Artificial Intelligence Models for Extracting Oncologic Outcomes from Japanese Electronic Health Records
KAN Matsumoto, K Togo, N Yonemoto, EOL Xu… - 2022
多施設電子カルテデータベースを用いた肺がん患者における薬物治療効果の評価: 非構造化データの自然言語処理
荒木賢二， 松元信弘， 東郷香苗， 米本直裕， 大木恵美子… - 医療情報学, 2023 - jstage.jst.go.jp
抄録 多施設の電子カルテなどの電子健康記録 (EHR) データベースを用いて,
肺がん患者の薬物治療効果を非構造化データより自然言語処理で抽出する方法を検討した …
肺がん患者の薬物治療効果を非構造化データより自然言語処理で抽出する方法を検討した …