記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：Studies in Health Technology and Informatics  

Predicting important outcomes in patients with complex medical conditions using multimodal electronic medical records remains challenge. We trained a machine learning model to predict the inpatient prognosis of cancer patients using EMR data with Japanese clinical text records, which has been considered difficult due to its high context. We confirmed high accuracy of the mortality prediction model using clinical text in addition to other clinical data, suggesting applicability of this method to cancer.

DOI： 10.3233/SHTI230276

Scopus

PubMed

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Respiratory Investigation  

Background: Therapeutic strategies in patients with interstitial pneumonia with autoimmune features (IPAF) and histological usual interstitial pneumonia (UIP) pattern (IPAF-UIP) have not been thoroughly evaluated. We compared the therapeutic efficacy of anti-fibrotic therapy with that of immunosuppressive treatment for patients with IPAF-UIP. Methods: In this retrospective case series, we identified consecutive IPAF-UIP patients treated with anti-fibrotic therapy or immunosuppressive therapy. Clinical characteristics, one-year treatment response, acute exacerbation, and survival were studied. We performed a stratified analysis by the pathological presence or absence of inflammatory cell infiltration. Results: Twenty-seven patients with anti-fibrotic therapy and 29 with immunosuppressive treatment were included. There was a significant difference in one-year forced vital capacity (FVC) change between patients with anti-fibrotic treatment (4 in 27 improved, 12 stable, and 11 worsened) and those with immunosuppressive treatment (16 in 29 improved, eight stable, and five worsened) (p = 0.006). There was also a significant difference in one-year St George's Respiratory Questionnaire (SGRQ) change between patients with anti-fibrotic therapy (2 in 27 improved, ten stable, and 15 worsened) and those with immunosuppressive treatment (14 in 29 improved, 12 stable, and worsened) (p < 0.001). There was no significant difference in survival between the groups (p = 0.32). However, in the subgroup with histological inflammatory cell infiltration, survival was significantly better with immunosuppressive therapy (p = 0.02). Conclusion: In IPAF-UIP, immunosuppressive therapy seemed to be superior to anti-fibrotic treatment in terms of therapeutic response, and provided better outcomes in the histological inflammatory subgroup. Further prospective studies are needed to clarify the therapeutic strategy in IPAF-UIP.

DOI： 10.1016/j.resinv.2023.01.007

Web of Science

Scopus

PubMed

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Respirology  

Background and objective: The development of clinically progressive fibrosis complicates a wide array of interstitial lung diseases (ILDs). However, there are limited data regarding its prevalence and prognosis. Methods: We analysed consecutive patients seen for initial evaluation of a fibrosing form of ILD (FILD). Patients were evaluated for evidence of progressive fibrosis over the first 24 months of follow-up. We defined a progressive phenotype as the presence of at least one of the following: a relative decline in forced vital capacity (FVC) of ≥10%; a relative decline in FVC of ≥5%–<10% with a relative decline in diffusing capacity of the lung for carbon monoxide of ≥15%, increased fibrosis on HRCT or progressive symptoms. Results: Eight hundred and forty-four patients (397 with idiopathic pulmonary fibrosis [IPF] and 447 non-IPF FILD) made up the final analysis cohort. Three hundred and fifty-five patients (42.1%) met the progressive phenotype criteria (59.4% of IPF patients and 26.6% of non-IPF FILD patients, p <0.01). In both IPF and non-IPF FILD, transplantation-free survival differed between patients with a progressive phenotype and those without (p <0.01). Multivariable analysis showed that a progressive phenotype was an independent predictor of transplantation-free survival (hazard ratio [HR]: 3.36, 95% CI: 2.68–4.23, p <0.01). Transplantation-free survival did not differ between non-IPF FILD with a progressive phenotype and IPF (HR: 1.12, 95% CI: 0.85–1.48, p = 0.42). Conclusion: Over one-fourth of non-IPF FILD patients develop a progressive phenotype compared to approximately 60% of IPF patients. The survival of non-IPF FILD patients with a progressive phenotype is similar to IPF.

DOI： 10.1111/resp.14245

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PubMed

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Respiratory Investigation  

Background: The COPD Assessment Test (CAT) has been studied as a measure of health status in idiopathic pulmonary fibrosis (IPF) and interstitial lung disease associated with connective tissue disease. However, its prognostic value is unknown. The present study explored the association between CAT score and mortality in fibrotic interstitial lung disease (FILD), including IPF and other forms of ILD. Methods: We retrospectively analyzed 501 consecutive patients with FILD who underwent clinical assessment, including pulmonary function test and CAT. The association between CAT score and 3-year mortality was assessed using Cox proportional hazard analysis, Kaplan–Meier plots, and the log-rank test for trend. To handle missing data, the imputed method was used. Results: The patients’ median age was 68 years, and 320 were male (63.9%). Regarding CAT severity, 203 patients had a low impact level (score <10), 195 had a medium level (10–20), 80 had a high level (21–30), and 23 had a very high level (31–40). During the 3-year study period, 118 patients died. After adjusting for age, sex, forced vital capacity, diffusion capacity for carbon monoxide, IPF diagnosis, and usual interstitial pneumonia pattern on high-resolution computed tomography, the CAT score was significantly associated with 3-year mortality (hazard ratio in increments of 10 points: 1.458, 95% confidence interval 1.161–1.830; p < 0.001). In addition, patients with high and very high impact levels had twofold and threefold higher mortality risk than those with low levels, respectively. Conclusion: The CAT has prognostic value in FILD.

DOI： 10.1016/j.resinv.2021.07.007

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PubMed

記述言語：日本語   掲載種別：研究論文（研究会，シンポジウム資料等）   出版者・発行元：(一社)日本医療情報学会  

記述言語：日本語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：(一社)日本医療情報学会  

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Cancer Cell International  

Comprehensive analysis of omics data, such as genome, transcriptome, proteome, metabolome, and interactome, is a crucial technique for elucidating the complex mechanism of cancer onset and progression. Recently, a variety of new findings have been reported based on multi-omics analysis in combination with various clinical information. However, integrated analysis of multi-omics data is extremely labor intensive, making the development of new analysis technology indispensable. Artificial intelligence (AI), which has been under development in recent years, is quickly becoming an effective approach to reduce the labor involved in analyzing large amounts of complex data and to obtain valuable information that is often overlooked in manual analysis and experiments. The use of AI, such as machine learning approaches and deep learning systems, allows for the efficient analysis of massive omics data combined with accurate clinical information and can lead to comprehensive predictive models that will be desirable for further developing individual treatment strategies of immunotherapy and molecular target therapy. Here, we aim to review the potential of AI in the integrated analysis of omics data and clinical information with a special focus on recent advances in the discovery of new biomarkers and the future direction of personalized medicine in non-small lung cancer.

DOI： 10.1186/s12935-021-02165-7

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PubMed

記述言語：日本語   掲載種別：研究論文（国際会議プロシーディングス）  

Web of Science

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Respiratory Investigation  

Background: Pulmonary hypertension (PH) influences mortality in patients with interstitial lung disease (ILD). Almost all studies on patients with ILD, have focused on the clinical impact of pre-capillary PH on survival. Therefore, little is known about the influence of post-capillary PH. We aimed to assess the prevalence of post-capillary PH and its clinical impact on survival in patients with ILD, followed by comparison with pre-capillary PH. Methods: This retrospective study enrolled 1152 patients with ILD who were diagnosed with PH using right heart catheterization between May 2007 and December 2015. We analyzed the demographics and composite outcomes (defined as death from any cause or lung transplantation) of patients with post-capillary PH and compared them with patients with pre-capillary PH. Results: Thirty-two (20%) of the 157 patients with ILD-PH were diagnosed with post-capillary PH. Patients with post-capillary PH had significantly lower modified Medical Research Council scores, higher diffusion capacity for carbon monoxide, higher resting PaO2, lower pulmonary vascular resistance (PVR), and higher lowest oxygen saturation during the 6-min walk test compared to those with pre-capillary PH. Cardiovascular diseases were associated with a higher risk of mortality in patients with post-capillary PH. Multivariate Cox proportional hazards analysis demonstrated no significant difference between the composite outcomes in pre-capillary and post-capillary PH, while PVR and the ILD Gender-Age-Physiology Index were significantly associated with the composite outcome. Conclusions: We found that approximately one-fifth of patients with ILD-PH were diagnosed with post-capillary PH, and that PVR and not post-capillary PH was associated with mortality.

DOI： 10.1016/j.resinv.2020.12.010

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PubMed

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Journal of the American Medical Informatics Association  

Purpose: Location visualization is essential for locating people/objects, improving efficiency, and preventing accidents. In hospitals, Wi-Fi, Bluetooth low energy (BLE) Beacon, indoor messaging system, and similar methods have generally been used for tracking, with Wi-Fi and BLE being the most common. Recently, nurses are increasingly using mobile devices, such as smartphones and tablets, while shifting. The accuracy when using Wi-Fi or BLE may be affected by interference or multipath propagation. In this research, we evaluated the positioning accuracy of geomagnetic indoor positioning in hospitals. Materials and Methods: We compared the position measurement accuracy of a geomagnetic method alone, Wi-Fi alone, BLE beacons alone, geomagnetic plus Wi-Fi, and geomagnetic plus BLE in a general inpatient ward, using a geomagnetic positioning algorithm by GiPStech. The existing Wi-Fi infrastructure was used, and 20 additional BLE beacons were installed. Our first experiment compared these methods' accuracy for 8 test routes, while the second experiment verified a combined geomagnetic/BLE beacon method using 3 routes based on actual daily activities. Results: The experimental results demonstrated that the most accurate method was geomagnetic/BLE, followed by geomagnetic/Wi-Fi, and then geomagnetic alone. Discussion: The geomagnetic method's positioning accuracy varied widely, but combining it with BLE beacons reduced the average position error to approximately 1.2 m, and the positioning accuracy could be improved further. We believe this could effectively target humans (patients) where errors of up to 3 m can generally be tolerated. Conclusion: In conjunction with BLE beacons, geomagnetic positioning could be sufficiently effective for many in-hospital localization tasks.

DOI： 10.1093/jamia/ocaa204

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PubMed

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）  

その他リンク： https://dblp.uni-trier.de/rec/conf/amia/2021

記述言語：日本語   掲載種別：記事・総説・解説・論説等（学術雑誌）   出版者・発行元：(有)科学評論社  

担当区分：筆頭著者,　最終著者,　責任著者   記述言語：日本語   掲載種別：記事・総説・解説・論説等（学術雑誌）  

CiNii Research

担当区分：筆頭著者,　最終著者,　責任著者   記述言語：日本語   掲載種別：記事・総説・解説・論説等（学術雑誌）   出版者・発行元：(株)総合医学社  

間質性肺炎(ILD)の正確な診断には、呼吸器内科医、放射線科医、病理医の集学的議論(MDD)、外科的肺生検やクライオバイオプシーが重要であるが、近年、新しいテクノロジーを用いた診療が広がりつつある。機械学習と深層学習を用いたILDの画像所見の抽出、ゲノム評価、診断と治療効果予測について概説した。また、間質性肺炎のAI(人工知能)創薬、遠隔診療(オンラインMDD診断)、在宅モニタリングと呼吸器リハビリテーションについて述べた。

担当区分：筆頭著者,　責任著者   記述言語：日本語   掲載種別：記事・総説・解説・論説等（商業誌、新聞、ウェブメディア）   出版者・発行元：株式会社　医学書院  

DOI： 10.11477/mf.1437200484

CiNii Research

記述言語：英語   掲載種別：研究発表ペーパー・要旨（国際会議）  

Web of Science

記述言語：日本語   掲載種別：研究発表ペーパー・要旨（全国大会，その他学術会議）   出版者・発行元：(一社)日本呼吸器学会  

J-GLOBAL

記述言語：日本語   掲載種別：研究発表ペーパー・要旨（全国大会，その他学術会議）  

J-GLOBAL

担当区分：筆頭著者,　責任著者   記述言語：日本語   掲載種別：研究発表ペーパー・要旨（全国大会，その他学術会議）  

J-GLOBAL

記述言語：日本語   掲載種別：研究発表ペーパー・要旨（全国大会，その他学術会議）  

J-GLOBAL

記述言語：日本語   掲載種別：記事・総説・解説・論説等（商業誌、新聞、ウェブメディア）  

CiNii Research

開催年月日： 2022年7月

記述言語：日本語   会議種別：口頭発表（招待・特別）  

開催年月日： 2022年4月

記述言語：日本語   会議種別：シンポジウム・ワークショップ パネル（指名）  

開催年月日： 2022年4月

記述言語：日本語   会議種別：口頭発表（招待・特別）  

開催年月日： 2021年4月

記述言語：日本語   会議種別：口頭発表（招待・特別）  

開催年月日： 2023年9月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2023年6月 - 2023年7月

記述言語：日本語   会議種別：口頭発表（一般）  

開催年月日： 2023年6月

記述言語：日本語   会議種別：ポスター発表  

開催年月日： 2023年6月

記述言語：日本語  

開催年月日： 2023年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2023年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2023年4月

記述言語：日本語   会議種別：口頭発表（一般）  

開催年月日： 2022年12月

記述言語：日本語   会議種別：口頭発表（一般）  

開催年月日： 2022年11月

記述言語：英語   会議種別：口頭発表（一般）  

開催年月日： 2022年11月

記述言語：日本語   会議種別：ポスター発表  

開催年月日： 2022年10月

記述言語：日本語   会議種別：ポスター発表  

開催年月日： 2022年6月

記述言語：日本語   会議種別：口頭発表（一般）  

開催年月日： 2022年6月

記述言語：日本語   会議種別：口頭発表（一般）  

開催年月日： 2021年11月

会議種別：口頭発表（一般）  

記述言語：日本語   会議種別：ポスター発表  

<p>医療現場における機械学習の応用による医師の治療支援や患者の個別化医療が近年多数報告されているなか、病院内に蓄積された患者の診療データを用い学習を進め、患者の予後予測を行う活用法は一つの大きなトピックである。一般にこういったタスクでは、入院から3日間など指定された期間の入院情報を用いて、予測したい将来時点における目的変数を予測する。しかし、入院初期から予測する将来時点までの期間が長いと予測が困難となる場合がある。 そこで、予測する将来時点より前における食事量などの患者状態を用いることが出来れば、目的変数に対する予測性能が向上すると考えられる。学習時にはこれらの状態も参照できるため、予測モデルを追加で構築することが可能である。本研究では、患者の入院経過を予測し、それをモデルの新たな特徴量として用いる予後予測手法を提案する。 本研究では、統合診療支援プラットフォームCITA Clinical Finderに集約された院内データを網羅的に用いて、肺炎患者を対象とした院内死亡と長期入院を予測する実験により本手法の有効性を確認した。</p>

DOI： 10.11517/pjsai.jsai2022.0_3yin228

CiNii Research

記述言語：英語   会議種別：口頭発表（一般）  

DOI： 10.1183/13993003.congress-2022.342

記述言語：英語   会議種別：口頭発表（一般）  

出願人：国立大学法人東海国立大学機構名古屋大学

出願番号：特願2022-1388808  出願日：2022年8月

出願番号：特願2022-043291  出願日：2022年3月

出願人：国立研究開発法人理化学研究所

出願番号：特願2019-094757  出願日：2019年5月

公開番号：特開2020-188872  公開日：2020年11月

特許番号/登録番号：特許第7334900号  登録日：2023年8月 

J-GLOBAL