Introduction of AI Technology for Objective Physical Function Assessment
Objective physical function assessment is crucial for determining patient eligibility for treatment and adjusting the treatment intensity. Existing assessments, such as performance status, are not well standardized, despite their frequent use in daily clinical practice. This paper explored how artif...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Bioengineering |
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| Online Access: | https://www.mdpi.com/2306-5354/11/11/1154 |
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| author | Nobuji Kouno Satoshi Takahashi Masaaki Komatsu Yusuke Sakaguchi Naoaki Ishiguro Katsuji Takeda Kyoko Fujioka Ayumu Matsuoka Maiko Fujimori Ryuji Hamamoto |
| author_facet | Nobuji Kouno Satoshi Takahashi Masaaki Komatsu Yusuke Sakaguchi Naoaki Ishiguro Katsuji Takeda Kyoko Fujioka Ayumu Matsuoka Maiko Fujimori Ryuji Hamamoto |
| author_sort | Nobuji Kouno |
| collection | DOAJ |
| description | Objective physical function assessment is crucial for determining patient eligibility for treatment and adjusting the treatment intensity. Existing assessments, such as performance status, are not well standardized, despite their frequent use in daily clinical practice. This paper explored how artificial intelligence (AI) could predict physical function scores from various patient data sources and reviewed methods to measure objective physical function using this technology. This review included relevant articles published in English that were retrieved from PubMed. These studies utilized AI technology to predict physical function indices from patient data extracted from videos, sensors, or electronic health records, thereby eliminating manual measurements. Studies that used AI technology solely to automate traditional evaluations were excluded. These technologies are recommended for future clinical systems that perform repeated objective physical function assessments in all patients without requiring extra time, personnel, or resources. This enables the detection of minimal changes in a patient’s condition, enabling early intervention and enhanced outcomes. |
| format | Article |
| id | doaj-art-ccb10fb21eb340f1a6058ec5ea14eda6 |
| institution | OA Journals |
| issn | 2306-5354 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Bioengineering |
| spelling | doaj-art-ccb10fb21eb340f1a6058ec5ea14eda62025-08-20T02:08:08ZengMDPI AGBioengineering2306-53542024-11-011111115410.3390/bioengineering11111154Introduction of AI Technology for Objective Physical Function AssessmentNobuji Kouno0Satoshi Takahashi1Masaaki Komatsu2Yusuke Sakaguchi3Naoaki Ishiguro4Katsuji Takeda5Kyoko Fujioka6Ayumu Matsuoka7Maiko Fujimori8Ryuji Hamamoto9Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, JapanDivision of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, JapanDivision of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, JapanDivision of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, JapanCancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, JapanCancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, JapanDivision of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, JapanDivision of Survivorship Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, JapanDivision of Survivorship Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, JapanDivision of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, JapanObjective physical function assessment is crucial for determining patient eligibility for treatment and adjusting the treatment intensity. Existing assessments, such as performance status, are not well standardized, despite their frequent use in daily clinical practice. This paper explored how artificial intelligence (AI) could predict physical function scores from various patient data sources and reviewed methods to measure objective physical function using this technology. This review included relevant articles published in English that were retrieved from PubMed. These studies utilized AI technology to predict physical function indices from patient data extracted from videos, sensors, or electronic health records, thereby eliminating manual measurements. Studies that used AI technology solely to automate traditional evaluations were excluded. These technologies are recommended for future clinical systems that perform repeated objective physical function assessments in all patients without requiring extra time, personnel, or resources. This enables the detection of minimal changes in a patient’s condition, enabling early intervention and enhanced outcomes.https://www.mdpi.com/2306-5354/11/11/1154objective physical function assessmentshort physical performance batterytimed up and gowalking speedgrip strengthmachine learning |
| spellingShingle | Nobuji Kouno Satoshi Takahashi Masaaki Komatsu Yusuke Sakaguchi Naoaki Ishiguro Katsuji Takeda Kyoko Fujioka Ayumu Matsuoka Maiko Fujimori Ryuji Hamamoto Introduction of AI Technology for Objective Physical Function Assessment Bioengineering objective physical function assessment short physical performance battery timed up and go walking speed grip strength machine learning |
| title | Introduction of AI Technology for Objective Physical Function Assessment |
| title_full | Introduction of AI Technology for Objective Physical Function Assessment |
| title_fullStr | Introduction of AI Technology for Objective Physical Function Assessment |
| title_full_unstemmed | Introduction of AI Technology for Objective Physical Function Assessment |
| title_short | Introduction of AI Technology for Objective Physical Function Assessment |
| title_sort | introduction of ai technology for objective physical function assessment |
| topic | objective physical function assessment short physical performance battery timed up and go walking speed grip strength machine learning |
| url | https://www.mdpi.com/2306-5354/11/11/1154 |
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