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 Research  

Background: Extracellular mitochondrial DNA (mtDNA) is released from damaged cells and increases in the serum and bronchoalveolar lavage fluid (BALF) of idiopathic pulmonary fibrosis (IPF) patients. While increased levels of serum mtDNA have been reported to be linked to disease progression and the future development of acute exacerbation (AE) of IPF (AE-IPF), the clinical significance of mtDNA in BALF (BALF-mtDNA) remains unclear. We investigated the relationships between BALF-mtDNA levels and other clinical variables and prognosis in IPF. Methods: Extracellular mtDNA levels in BALF samples collected from IPF patients were determined using droplet-digital PCR. Levels of extracellular nucleolar DNA in BALF (BALF-nucDNA) were also determined as a marker for simple cell collapse. Patient characteristics and survival information were retrospectively reviewed. Results: mtDNA levels in serum and BALF did not correlate with each other. In 27 patients with paired BALF samples obtained in a stable state and at the time of AE diagnosis, BALF-mtDNA levels were significantly increased at the time of AE. Elevated BALF-mtDNA levels were associated with inflammation or disordered pulmonary function in a stable state (n = 90), while being associated with age and BALF-neutrophils at the time of AE (n = 38). BALF-mtDNA ≥ 4234.3 copies/µL in a stable state (median survival time (MST): 42.4 vs. 79.6 months, p < 0.001) and ≥ 11,194.3 copies/µL at the time of AE (MST: 2.6 vs. 20.0 months, p = 0.03) were associated with shorter survival after BALF collection, even after adjusting for other known prognostic factors. On the other hand, BALF-nucDNA showed different trends in correlation with other clinical variables and did not show any significant association with survival time. Conclusions: Elevated BALF-mtDNA was associated with a poor prognosis in both IPF and AE-IPF. Of note, at the time of AE, it sharply distinguished survivors from non-survivors. Given the trends shown by analyses for BALF-nucDNA, the elevation of BALF-mtDNA might not simply reflect the impact of cell collapse. Further studies are required to explore the underlying mechanisms and clinical applications of BALF-mtDNA in IPF.

DOI： 10.1186/s12931-024-02828-9

Open Access

Web of Science

Scopus

PubMed

担当区分：筆頭著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Thorax  

Background Pulmonary hypertension (PH) is defined by elevated mean pulmonary arterial pressure (MPAP), and elevated pulmonary vascular resistance (PVR) reflects pulmonary vascular abnormalities. The clinical significance of non-severe PH in patients with various interstitial lung diseases (ILDs) has not been fully elucidated. We aimed to investigate the clinical significance of MPAP and PVR for mortality in patients with newly diagnosed ILD. Methods We retrospectively analysed consecutive patients with ILD at initial evaluations that included right heart catheterisation from 2007 to 2018. These patients were classified by MPAP and PVR using the 2022 the European Society of Cardiology (ESC)/the European Respiratory Society (ERS) guidelines for PH. The clinical significance of MPAP and PVR for mortality was analysed. Results Among 854 patients, 167 (19.6%) had MPAP>20 mm Hg. The proportion of patients with PVR>2 Wood units (WU) among those with MPAP≤20 mm Hg, 20<MPAP<25 mm Hg, and ≥25 mm Hg were 26.2%, 60.4% and 86.4%, respectively. In Cox proportional hazards analyses with adjustment for ILD–Gender, Age and Physiology Index, PVR but not MPAP was associated with a higher mortality rate (HR 1.37, 95% CI 1.23 to 1.52, p<0.0001; HR 0.98, 95% CI 0.96 to 1.01, p=0.1671, respectively). PVR>2 WU was associated with a higher mortality rate (HR 1.61, 95% CI 1.28 to 2.02, p<0.0001) even in a group with MPAP≤20 mm Hg. Conclusions Mild elevation of PVR was associated with a higher mortality rate in patients with newly diagnosed ILD, even in those with MPAP≤20 mm Hg.

DOI： 10.1136/thorax-2023-220179

Web of Science

Scopus

PubMed

担当区分：筆頭著者,　責任著者   記述言語：日本語   掲載種別：研究論文（学術雑誌）  

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

Objectives: In this study we aimed to develop an artificial intelligence-based model for predicting postendoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP). Methods: We retrospectively reviewed ERCP patients at Nagoya University Hospital (NUH) and Toyota Memorial Hospital (TMH). We constructed two prediction models, a random forest (RF), one of the machine-learning algorithms, and a logistic regression (LR) model. First, we selected features of each model from 40 possible features. Then the models were trained and validated using three fold cross-validation in the NUH cohort and tested in the TMH cohort. The area under the receiver operating characteristic curve (AUROC) was used to assess model performance. Finally, using the output parameters of the RF model, we classified the patients into low-, medium-, and high-risk groups. Results: A total of 615 patients at NUH and 544 patients at TMH were enrolled. Ten features were selected for the RF model, including albumin, creatinine, biliary tract cancer, pancreatic cancer, bile duct stone, total procedure time, pancreatic duct injection, pancreatic guidewire-assisted technique without a pancreatic stent, intraductal ultrasonography, and bile duct biopsy. In the three fold cross-validation, the RF model showed better predictive ability than the LR model (AUROC 0.821 vs. 0.660). In the test, the RF model also showed better performance (AUROC 0.770 vs. 0.663, P = 0.002). Based on the RF model, we classified the patients according to the incidence of PEP (2.9%, 10.0%, and 23.9%). Conclusion: We developed an RF model. Machine-learning algorithms could be powerful tools to develop accurate prediction models.

DOI： 10.1111/den.14622

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：Journal of Pain and Symptom Management  

Context: Early palliative care is recommended within eight-week of diagnosing advanced cancer. Although guidelines suggest routine screening to identify cancer patients who could benefit from palliative care, implementing screening can be challenging due to understaffing and time constraints. Objectives: To develop and evaluate machine learning models for predicting specialist palliative care needs in advanced cancer patients undergoing chemotherapy, and to investigate if predictive models could substitute screening tools. Methods: We conducted a retrospective cohort study using supervised machine learning. The study included patients aged 18 or older, diagnosed with metastatic or stage IV cancer, who underwent chemotherapy and distress screening at a designated cancer hospital in Japan from April 1, 2018, to March 31, 2023. Specialist palliative care needs were assessed based on distress screening scores and expert evaluations. Data sources were hospital's cancer registry, health claims database, and nursing admission records. The predictive model was developed using XGBoost, a machine learning algorithm. Results: Out of the 1878 included patients, 561 were analyzed. Among them, 114 (20.3%) exhibited needs for specialist palliative care. After under-sampling to address data imbalance, the models achieved an Area Under the Curve (AUC) of 0.89 with 95.8% sensitivity and a specificity of 71.9%. After feature selection, the model retained five variables, including the patient-reported pain score, and showcased an 0.82 AUC. Conclusion: Our models could forecast specialist palliative care needs for advanced cancer patients on chemotherapy. Using five variables as predictors could replace screening tools and has the potential to contribute to earlier palliative care.

DOI： 10.1016/j.jpainsymman.2024.01.009

Open Access

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：Journal of Pain and Symptom Management  

The authors regret that the affiliation of M.H., S.Y., M.H., and A.K. was listed as the Department of Clinical Oncology and Chemotherapy at Nagoya University Hospital in Nagoya, Japan. This should have been listed as the Department of Nursing at Nagoya University Hospital in Nagoya, Japan. The authors would like to apologize for any inconvenience caused.

DOI： 10.1016/j.jpainsymman.2024.05.019

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：Frontiers in Medicine  

Background: Health-related quality of life (HRQoL) captures different aspects of the fibrotic interstitial lung disease (FILD) evaluation from the patient’s perspective. However, little is known about how HRQoL changes in patients with non-idiopathic pulmonary fibrosis (IPF) FILD, especially in those with progressive pulmonary fibrosis (PPF). The aim of this study is to clarify whether HRQoL deteriorates in patients with non-IPF FILD and to evaluate the differences in the changes in HRQoL between those with and without PPF. Methods: We collected data from consecutive patients with non-IPF FILD and compared annual changes in HRQoL over 2 years between patients with PPF and those without. The St George’s respiratory questionnaire (SGRQ) and COPD assessment test (CAT) were used to assess HRQoL. Changes in the SGRQ and CAT scores for 24 months from baseline were evaluated with a mixed-effect model for repeated measures. Results: A total of 396 patients with non-IPF FILD were reviewed. The median age was 65 years and 202 were male (51.0%). The median SGRQ and CAT scores were 29.6 and 11, respectively. Eighty-six (21.7%) showed PPF. Both SGRQ and CAT scores were significantly deteriorated in patients with PPF compared to those without PPF (p < 0.01 for both). Clinically important deterioration in the SGRQ and CAT scores were observed in 40.0 and 35.7% of patients with PPF and 11.7 and 16.7% of those without, respectively. PPF was significantly associated with clinically important deterioration in the SGRQ score (odds ratio 5.04; 95%CI, 2.61–9.76, p < 0.01) and CAT score (odds ratio 2.78; 95%CI, 1.27–6.06, p = 0.02). Conclusion: The SGRQ and CAT scores were significantly deteriorated in patients with non-IPF FILD and PPF. Considering an evaluation of HRQoL would be needed when assessing PPF.

DOI： 10.3389/fmed.2023.1067149

Open Access

Web of Science

Scopus

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）   出版者・発行元：Elsevier BV  

DOI： 10.1016/j.gie.2023.04.1087

担当区分：筆頭著者   記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）   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（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

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：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

Web of Science

Scopus

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

Open Access

Web of Science

Scopus

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

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：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

Open Access

Web of Science

Scopus

PubMed

担当区分：筆頭著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：European Respiratory Journal  

DOI： 10.1183/13993003.01346-2020

Web of Science

Scopus

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 著書種別：学術書

記述言語：日本語 著書種別：学術書

記述言語：日本語 著書種別：学術書

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。

記述言語：日本語 著書種別：学術書

記述言語：日本語 著書種別：学術書

＜文献概要＞Point ・テクノロジーの発展に伴って医療AIも開発されてきたが,臨床応用は注意が必要である.・間質性肺炎の画像特徴を捉えるAIから,診断・予後予測AIも開発されてきた.・全国規模の間質性肺炎レジストリが進行中であり,様々な研究結果が期待される.

その他リンク： https://search.jamas.or.jp/index.php?module=Default&action=Link&pub_year=2021&ichushi_jid=J06862&link_issn=&doc_id=20210813210020&doc_link_id=10.11477%2Fmf.1437200484&url=https%3A%2F%2Fdoi.org%2F10.11477%2Fmf.1437200484&type=%88%E3%8F%91.jp_%83I%81%5B%83%8B%83A%83N%83Z%83X&icon=https%3A%2F%2Fjk04.jamas.or.jp%2Ficon%2F00024_2.gif

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：一般社団法人 人工知能学会  

<p>病院では電子カルテや看護録など様々な医療文書が蓄積されている。本研究では医療従事者による文書探索を支援するために、医療文書群から臨床的に重要な文の抽出を目指す。学習データがない場合に用いられる教師なし文書要約手法は、文書全体の内容を網羅するために、文書中の多くの文と類似する文を取得する。しかし、医療文書では網羅性よりも臨床的な重要度が重視されるため、適しているとは限らない。一方、ある患者に対して蓄積された診療データを元に、その患者の将来における状態である予後を予測する予後予測の研究が取り組まれている。予後予測モデルで予測した患者の予後が悪い場合、その入力情報は予後の悪化につながる状態や事象を表しており、臨床的に重要であると考えられる。本研究ではこの考えに基づいて、予後予測モデルの出力値を臨床的に重要な文の指標とみなした重要文抽出手法を提案する。実験では名古屋大学医学部附属病院に集約された診療データで学習した予後予測モデルを利用して重要文抽出モデルを構築した。入院ごとに重要文抽出モデルで文をランキングし、それと臨床的に重要な情報を記載した文書を比較することで手法の有効性を示した。</p>

DOI： 10.11517/pjsai.jsai2023.0_3xin404

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）   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

Web of Science

Scopus

PubMed

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：(有)科学評論社  

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)日本医事新報社  

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）   出版者・発行元：(有)科学評論社  

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  

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（商業誌、新聞、ウェブメディア）  

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。

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)日本医療情報学会  

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（全国大会，その他学術会議）  

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

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：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,　最終著者,　責任著者   記述言語：日本語   掲載種別：書評論文，書評，文献紹介等  

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： 2025年3月

記述言語：日本語   会議種別：口頭発表（一般）  

開催年月日： 2024年11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： 2024年9月

記述言語：英語   会議種別：口頭発表（一般）  

開催年月日： 2024年9月

記述言語：英語   会議種別：口頭発表（一般）  

DOI： 10.1183/13993003.congress-2024.OA2863

開催年月日： 2024年8月

記述言語：英語   会議種別：ポスター発表  

By linking medical real-world data with geographic information, it is possible to evaluate the impact on hospitalization based on these characteristics, such as patient residence information and disease and medical information. In this study, environmental exposure to air pollutants was reported as a risk factor, and predictive models were used to examine factors affecting health. The importance of the characteristics appeared according to the disease, and overall, the patient profile at the time of admission, such as ADL, was shown to be high, but for respiratory diseases, the cumulative concentration of air pollutants NO2, SPM, and NOx for one year before the onset of admission was the top risk factor for long-term hospitalization, suggesting the influence of exposure due to environmental factors.

開催年月日： 2024年6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： 2024年6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： 2024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： 2024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： 2024年3月

記述言語：日本語   会議種別：口頭発表（一般）  

開催年月日： 2024年2月

記述言語：英語   会議種別：口頭発表（一般）  

開催年月日： 2024年

記述言語：日本語   会議種別：口頭発表（一般）  

開催年月日： 2023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： 2023年10月

記述言語：日本語   会議種別：公開講演，セミナー，チュートリアル，講習，講義等  

開催年月日： 2023年9月 - 2023年10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： 2023年9月 - 2023年10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9月

記述言語：英語   会議種別：ポスター発表  

DOI： 10.1183/13993003.congress2023.PA434

開催年月日： 2023年9月

記述言語：英語   会議種別：口頭発表（一般）  

DOI： 10.1183/13993003.congress-2023.OA1424

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  

DOI： 10.1183/13993003.congress-2023.PA1236

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6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： 2023年2月

記述言語：英語   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： 2023年2月

記述言語：英語   会議種別：口頭発表（招待・特別）  

開催年月日： 2023年2月

記述言語：英語   会議種別：口頭発表（一般）  

開催年月日： 2023年2月

記述言語：英語   会議種別：口頭発表（一般）  

開催年月日： 2023年2月

記述言語：英語   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： 2023年2月

記述言語：英語   会議種別：口頭発表（一般）  

開催年月日： 2023年2月

記述言語：英語   会議種別：口頭発表（一般）  

開催年月日： 2023年2月

記述言語：英語   会議種別：口頭発表（招待・特別）  

開催年月日： 2023年2月

記述言語：英語   会議種別：口頭発表（招待・特別）  

開催年月日： 2023年

記述言語：英語   会議種別：ポスター発表  

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

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9月

記述言語：英語   会議種別：口頭発表（一般）  

DOI： 10.1183/13993003.congress-2022.342

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）  

開催年月日： 2021年11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： 2021年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2021年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2021年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2021年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2021年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2021年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2021年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2021年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2021年5月

記述言語：英語   会議種別：ポスター発表  

開催年月日： 2021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： 2021年

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： 2021年

記述言語：日本語   会議種別：口頭発表（一般）  

開催年月日： 2021年

記述言語：日本語   会議種別：ポスター発表  

開催年月日： 2021年

記述言語：日本語   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）  

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）  

DOI： 10.15032/jsrcr.34.supplement_81s_1

CiNii Research

出願人：国立大学法人東海国立大学機構

出願番号：特願2023-109002  出願日：2023年7月

出願人：富士フイルム株式会社

出願番号：特願2023-030561  出願日：2023年2月

公開番号：特開2024-035034  公開日：2024年3月

J-GLOBAL

出願人：富士フイルム株式会社

出願番号：特願2022-138808  出願日：2022年8月

公開番号：特開2024-034529  公開日：2024年3月

J-GLOBAL

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2022-1388807  出願日：2022年8月

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