データと医療を繋げ、世界を変える

TXP主導の研究 - TXP所属の医師がデータ解析と論文執筆を主導した研究

TXPの医師が参画した研究 - TXPとの共同研究またはTXPの医師が外部研究者として参画した研究

2024年8月現在／Googleスプレッドシートに遷移します。

2022年

（分担）ドネペジルのドラッグリポジショニングによるCOVID-19後遺症治療薬の開発 －精神症状治療薬へのリポジショニング－
国立研究開発法人日本医療研究開発機構(AMED)

2021年

（分担）救急遠隔医療システムの応用により病院前から院内及び多施設間までのシームレスな情報共有を図り重症化を予防するための医療機器システムの開発
国立研究開発法人 日本医療研究開発機構(AMED) 医療機器等における先進的研究開発・開発体制強靭化事業 (基盤技術開発プロジェクト) 応用フェーズの研究開発課題

2018年

（代表研究者 園生智弘）AIホスピタル事業
国立研究開発法人 医薬基盤健康栄養研究所：戦略的イノベーション創造プログラム（SIP）

1. Sato M, Goto T. Dose reduction of olaparib in older patients: Insights from an analysis of a National Database in Japan. J Obstet Gynaecol Res. 2023 Dec;49(12):2889-2893.

2. Yasuda M, Saito A, Goto T, Yamamoto R, Liu K, Kuriyama A, Kondo Y, Kasugai D; RED‐PAM study investigators. Challenges hindering emergency physicians; involvement in multicenter collaborative studies in Japan: A nationwide survey analysis. Acute Med Surg. 2023 Nov 23;10(1):e906.

3. Ito N, Kadomatsu S, Fujisawa M, Fukaguchi K, Ishizawa R, Kanda N, Kasugai D, Nakajima M, Goto T, Tsugawa Y. The Accuracy and Potential Racial and Ethnic Biases of GPT-4 in the Diagnosis and Triage of Health Conditions: Evaluation Study. JMIR Med Educ. 2023 Nov 2;9:e47532.

4. Nakajima M, Okada Y, Sonoo T, Goto T. Development and Validation of a Novel Method for Converting the Japan Coma Scale to Glasgow Coma Scale. J Epidemiol. 2023 Oct 5;33(10):531-535.

5. (Letter) Kasugai D, Nakashima T, Goto T. Clinical implications of urine output-based sepsis-associated acute kidney injury. Intensive Care Med. 2023 Oct;49(10):1263-1265

6. Shibata J, Okada Y, Osawa I, Shiraishi A, Goto T. Trauma mechanisms and patterns of blunt cervical vascular injury: A descriptive study using a nationwide trauma registry. Am J Emerg Med. 2023 Sep;71:117-122.

7. Takahashi M, Ogura K, Goto T, Hayakawa M. Electrocardiogram monitoring as a predictor of neurological and survival outcomes in patients with out-of-hospital cardiac arrest: a single-center retrospective observational study. Front Neurol. 2023 Jul 4;14:1210491.

8. Shibata J, Osawa I, Fukuchi K, Goto T. The Association Between Time From Emergency Department Visit to ICU Admission and Mortality in Patients With Sepsis. Crit Care Explor. 2023 May 9;5(5):e0915.

9. Saito A, Osawa I, Shibata J, Sonoo T, Nakamura K, Goto T. The prognostic utility of prehospital qSOFA in addition to emergency department qSOFA for sepsis in patients with suspected infection: A retrospective cohort study. PLoS One. 2023 Feb 24;18(2):e0282148.

10.Okuma A, Nakajima M, Sonoo T, Nakamura K, Goto T. Association between comorbid mental illness and preceding emergency department visits in unplanned admissions. Acute Med Surg. 2023 Jan 18;10(1):e814

11. Nakamura K, Ogura K, Nakano H, Ikechi D, Mochizuki M, Takahashi Y, Goto T. Explorative Clustering of the Nitrogen Balance Trajectory in Critically Ill Patients: A Preliminary post hoc Analysis of a Single-Center Prospective Observational Study. Ann Nutr Metab. 2023;79(5):460-468

12. Fukaguchi K, Goto T, Yamamoto T, Yamagami H. Experimental Implementation of NSER Mobile App for Efficient Real-Time Sharing of Prehospital Patient Information With Emergency Departments: Interrupted Time-Series Analysis. JMIR Form Res. 2022;6(7):e37301.

13. Fujimori R, Liu K, Soeno S, Naraba H, Ogura K, Hara K, Sonoo T, Ogura T, Nakamura K, Goto T. Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence-Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation. JMIR Form Res. 2022;6(6):e36501.

14. Fukuchi K, Osawa I, Satake S, Ito H, Shibata J, Dohi E, Kasugai D, Miyamoto Y, Ohbe H, Tamoto M, Yamada K, Yoshikawa K, Goto T. The Contribution of Chest X-Ray to Predict Extubation Failure in Mechanically Ventilated Patients Using Machine Learning-Based Algorithms. Crit Care Explor. 2022;4(6):e0718

15. Liu K, Shibata J, Fukuchi K, Takahashi K, Sonoo T, Ogura T, Goto T.Optimal timing of introducing mobilization therapy for ICU patients with sepsis. J Intensive Care. 2022;10(1):22.

16. Okada Y, Okada A, Ito H, et al. External validation of the POP score for predicting obstetric and gynecological diseases in the emergency department. Am J Emerg Med. 2021;51:348-353

17. Shibata J , Osawa I, Soeno S, et al. Risk factors of sepsis among patients with qSOFA<2 in the emergency department. Am J Emerg Med 2021;50:699-706

18. Naraba H. Goto T. Tokuda M. et al. Accuracy and stability of a subcutaneous flash glucose monitoring system in critically ill patient. J Diabetes Sci Technol. Jun 11:19322968211017203.

19. Fukaguchi K, Yamagami H, Soeno S. et al. Association of Initial Potassium Levels with the Type of Stroke in the Emergency Department. J Stroke Cerebrovasc Dis. 2021;30(8):105875.

20. Naraba H, Goto T, Shirakawa T et al. Time in blood glucose range 70 to 180 mg/dL and survival rate in critically ill patients: A retrospective cohort study. PLOS One. 2021;16(5):e0252158.

21. Osawa I, Sonoo T, Soeno S, Hara K, Nakamura K, and Goto T. Clinical performance of early warning scoring systems for identifying sepsis among anti-hypertensive agent users. Am J Emerg Med. 2021;48:120-127

22. Soeno S, Hara K, Fujimori R, Hashimoto K, Shirakawa T, Sonoo T, Nakamura K, Goto T. Initial assessment in emergency departments by chief complaint and respiratory rate. J Gen Fam Med. 2021;22(4):202-208

23. Fukaguchi K, Goto T, Fukui H, Sekine I, Yamagami H. Reversible cerebral vasoconstriction syndrome: the importance of follow-up imaging within 2 weeks. Acute Med Surg. 2020;7(1):e559.

24. Osawa I, Goto T, Yamamoto Y, Tsugawa Y. Machine-learning-based prediction models for high-need high-cost patients using nationwide clinical and claims data. NPJ Digit Med. 2020;3(1):148.

25. Shirakawa T, Sonoo T, Ogura K, Fujimori R, Hara K, Goto T, Hashimoto H, Takahashi Y, Naraba H, Nakamura K. Institution-Specific Machine Learning Models for Prehospital Assessment to Predict Hospital Admission: Prediction Model Development Study. J Med Int Res Med Inform. 2020;8(10):e20324.

26. Goto T, Hara K, Hashimoto K, Soeno S, Shirakawa T, Sonoo T, Nakamura K. Validation of chief complaints, medical history, medications, and physician diagnoses structured with an integrated emergency department information system in Japan: the Next Stage ER system. Acute Med Surg. 2020;7(1):e554.

27. Nakamura K, Ogura K, Nakano H, Naraba H, Takahashi Y, Sonoo T, Hashimoto H, Goto T. Disseminated Intravascular Coagulopathy Is Associated with the Outcome of Persistent Inflammation, Immunosuppression and Catabolism Syndrome. J Clin Med. 2020;9(8):E2662.

28. Nakamura K, Ogura K, Nakano H, Naraba H, Takahashi Y, Sonoo T, Hashimoto H, Morimura N. C-reactive protein clustering to clarify persistent inflammation, immunosuppression and catabolism syndrome. Intensive Care Med. 2020;46(3):437-443.

1. Sugaya A, Naito K, Goto T, Hagiwara Y, Okamoto H, Watase H, Hasegawa K. First-Pass Success of Video Laryngoscope Compared With Direct Laryngoscope in Intubations Performed by Residents in the Emergency Department. Cureus. 2023;15(10):e47563.

2. Hata T, Goto T, Yamanaka S, Matsumoto T, Yamamura O, Hayashi H. Prognostic value of initial serum sodium level in predicting disease severity in patients with COVID-19: A multicenter retrospective study. J Infect Chemother. 2023:S1341-321X(23)00242-8.

3. Osawa I, Goto T, Kudo D, Hayakawa M, Yamakawa K, Kushimoto S, Foster DM, Kellum JA, Doi K. Targeted therapy using polymyxin B hemadsorption in patients with sepsis: a post-hoc analysis of the JSEPTIC-DIC study and the EUPHRATES trial. Crit Care. 2023:21;27(1):245.

4. Takahashi J, Goto T, Fujitani S, Okamoto H, Hagiwara Y, Watase H, Hasegawa K; Japanese Emergency Medicine Network Investigators. Association of airway obstruction with first-pass success and intubation-related adverse events in the emergency department: multicenter prospective observational studies. Front Med (Lausanne). 2023 May 25;10:1199750.

5. Ohbe H, Goto T, Okada A, Yasunaga H. Association between COVID-19 pandemic and mental disorders in spouses of intensive care unit patients. Intensive Care Med. 2023 Jan;49(1):112-114.

6. Osawa I, Goto T, Tabuchi T, Koga HK, Tsugawa Y. Machine-learning approaches to identify determining factors of happiness during the COVID-19 pandemic: retrospective cohort study. BMJ Open. 2022 Dec 16;12(12):e054862

7. Nakamura K, Ogura K, Ohbe H, Goto T. Clinical Criteria for Persistent Inflammation, Immunosuppression, and Catabolism Syndrome: An Exploratory Analysis of Optimal Cut-Off Values for Biomarkers. J Clin Med. 2022 Sep 29;11(19):5790.

8. Liu K, Nakamura K, Kudchadkar SR, Katsukawa H, Nydahl P, Ely EW, Takahashi K, Inoue S, Nishida O. Mobilization and Rehabilitation Practice in ICUs During the COVID-19 Pandemic. J Intensive Care Med. 2022 Sep;37(9):1256-1264.

9. ISARIC Clinical Characterization Group, Garcia-Gallo E, Merson L, Kennon K, Kelly S, Citarella BW, Fryer DV, Shrapnel S, Lee J, Duque S, Fuentes YV, Balan V, Smith S, Wei J, Gonçalves BP, Russell CD, Sigfrid L, Dagens A, Olliaro PL, Baruch J, Kartsonaki C, Dunning J, Rojek A, Rashan A, Beane A, Murthy S, Reyes LF. ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19. Sci Data. 2022;9(1):454.

10. Sugiura A, Shamekhi J, Goto T, Spieker M, Iliadis C, Kavsur R, Mauri V, Kelm M, Baldus S, Tanaka T, Tabata N, Sinning JM, Weber M, Zimmer S, Nickenig G, Westenfeld R, Pfister R, Becher MU; of the Heart Failure Network Rhineland. Early response of right-ventricular function to percutaneous mitral valve repair. Clin Res Cardiol. 2022;111(8):859-868.

11. Sakamoto T, Goto T, Fujiogi M, Kawarai Lefor A. Machine learning in gastrointestinal surgery. Surg Today. 2022;52(7):995-1007.

12. Nishimoto Y, Ohbe H, Matsui H, Nakajima M, Sasabuchi Y, Goto T, Morita K, Fushimi K, Sato Y, Yasunaga H. Predictive ability of the sequential organ failure assessment score for in-hospital mortality in patients with cardiac critical illnesses: a nationwide observational study. Eur Heart J Acute Cardiovasc Care. 2022;11(4):312-321

13. Okada A, Hashimoto Y, Goto T, Yamaguchi S, Ono S, Ikeda Kurakawa K, Nangaku M, Yamauchi T, Yasunaga H, Kadowaki T. A Machine Learning-Based Predictive Model to Identify Patients Who Failed to Attend a Follow-up Visit for Diabetes Care After Recommendations From a National Screening Program. Diabetes Care. 2022;45(6):1346-1354.

14. Ohbe H, Goto T, Nakamura K, Matsui H, Yasunaga H. Development and validation of early prediction models for new-onset functional impairment at hospital discharge of ICU admission. Intensive Care Med. 2022;48(6):679-689

15. Ohbe H, Goto T, Matsui H, Fushimi K, Yasunaga H. Associations of Government-issued ICU Admission Criteria with Clinical Practices, Outcomes, and ICU Bed Occupancy. Ann Am Thorac Soc. 2022;19(6):1013-1021

16. Goto T, Kudo D, Uchimido R, Hayakawa M, Yamakawa K, Abe T, Shiraishi A, Kushimoto S. Web-based application for predicting the potential target phenotype for recombinant human thrombomodulin therapy in patients with sepsis: analysis of three multicentre registries. Crit Care. 2022;26(1):145

17. Watanabe S, Liu K, Nakamura K, Kozu R, Horibe T, Ishii K, Yasumura D, Takahashi Y, Nanba T, Morita Y, Kanaya T, Suzuki S, Lefor AK, Katsukawa H, Kotani T. Association between Early Mobilization in the ICU and Psychiatric Symptoms after Surviving a Critical Illness: A Multi-Center Prospective Cohort Study. J Clin Med. 2022;11(9):2587.

18. Liu K, Nakamura K, Kudchadkar SR, Katsukawa H, Nydahl P, Ely EW, Takahashi K, Inoue S, Nishida O.J Intensive Care Med. Mobilization and Rehabilitation Practice in ICUs During the COVID-19 Pandemic. 2022 Apr 27:8850666221097644

19. Goto T, Oka S, Okamoto H, Hagiwara Y, Watase H, Hasegawa K. Association of Number of Physician Postgraduate Years With Patient Intubation Outcomes in the Emergency Department. JAMA Netw Open. 2022;5(4) e226622

20. Konishi T, Goto T, Fujiogi M, Michihata N, Kumazawa R, Matsui H, Fushimi K, Tanabe M, Seto Y, Yasunaga H. New machine learning scoring system for predicting postoperative mortality in gastroduodenal ulcer perforation: A study using a Japanese nationwide inpatient database. Surgery. 2022;171(4):1036-1042

21. Liu K, Kotani T, Nakamura K, Chihiro T, Morita Y, Ishii K, Fujizuka K, Yasumura D, Taniguchi D, Hamagami T, Shimojo N, Nitta M, Hongo T, Akieda K, Atsuo M, Kaneko T, Sakuda Y, Andoh K, Nagatomi A, Tanaka Y, Irie Y, Kamijo H, Hanazawa M, Kasugai D, Ayaka M, Oike K, Lefor AK, Takahashi K, Katsukawa H, Ogura T. Effects of evidence-based ICU care on long-term outcomes of patients with sepsis or septic shock (ILOSS): protocol for a multicentre prospective observational cohort study in Japan. BMJ Open. 2022;12(3):e054478.

22. Hama T, Ushijima A, Goto T, Nagamatsu H, Morita N, Yoshimachi F, Ikari Y, Kobayashi Y.J Effect of Cardiac Rehabilitation on Glomerular Filtration Rate Using Serum Cystatin C Concentration in Patients With Cardiovascular Disease and Renal Dysfunction. Cardiopulm Rehabil Prev. 2022;42(2):E15-E22.

23. Miyamoto Y, Matsuyama T, Goto T, Ohbe H, Kitamura T, Yasunaga H, Ohta B. Association between age and neurological outcomes in out-of-hospital cardiac arrest patients resuscitated with extracorporeal cardiopulmonary resuscitation: a nationwide multicentre observational study. Eur Heart J Acute Cardiovasc Care. 2022;11(1):35-42.

24. Nakano H, Naraba H, Hashimoto H, Mochizuki M, Takahashi Y, Sonoo T, Ogawa Y, Matsuishi Y, Shimojo N, Inoue Y, Nakamura K. Novel protocol combining physical and nutrition therapies, Intensive Goal-directed REhabilitation with Electrical muscle stimulation and Nutrition (IGREEN) care bundle. Crit Care. 2021;25(1):415.

25. Kudo D, Goto T, Uchimido R. et al. Coagulation phenotypes in sepsis and effects of recombinant human thrombomodulin: an analysis of three multicentre observational studies. Crit Care. 2021 19;25(1):114

26. Miyamoto Y, Ohbe H, Goto T, Yasunaga H. Association between intensive care unit admission of a patient and mental disorders in the spouse: a retrospective matched-pair cohort study. J Intensive Care. 2021;29;9(1):69

27. Liu K, Nakamura K, Katsukawa H, Nydahl P, Ely EW, Kudchadkar SR, Takahashi K, Elhadi M, Gurjar M, Leong BK, Chung CR, Balachandran J, Inoue S, Lefor AK, Nishida O.Front Med (Lausanne). Implementation of the ABCDEF Bundle for Critically Ill ICU Patients During the COVID-19 Pandemic: A Multi-National 1-Day Point Prevalence Study. 2021;8:735860.

28. Liu K, Nakamura K, Katsukawa H, et al. ABCDEF bundle and supportive intensive care unit practices for patients with COVID-19 infection: An international point prevalence study -The ISIIC Study-. Crit Care Explor. 2021;3(3):e0353

29. Sugiura A, Weber M, Tabata N, Goto T, Öztürk C, Lin M, Zimmer S, Nickenig G, Sinning JM. QRS duration is a risk indicator of adverse outcomes after MitraClip. Catheter Cardiovasc Interv. 2020;98(4):E594-E601.

30. Sugiura A, Weber M, Tabata N, Goto T, Grube E, Treede H, Werner N, Nickenig G, Sinning JM. Association of heart failure duration with clinical outcomes after transcatheter mitral valve repair for functional mitral regurgitation. Catheter Cardiovasc Interv. 2021;98(3):E412-E419.

31. Osawa I, Goto T, Asami Y, Itoh N, Kaga Y, Yamamoto Y, Tsugawa Y. Physician visits and medication prescriptions for major chronic diseases during the COVID-19 pandemic in Japan: retrospective cohort study. BMJ Open. 2021;11 (7) e050938

32. Ito Y, Goto T, Huh JY, Yamamura O, Hamano T, Kikuta KI, Hayashi H. Development of a Scoring System to Predict Prolonged Post-Stroke Dysphagia Remaining at Discharge from a Subacute Care Hospital to the Home. J Stroke Cerebrovasc Dis. 2021;30(7):105804

33. Katsukawa H, Ota K, Liu K, Morita Y, Watanabe S, Sato K, Ishii K, Yasumura D, Takhamaahashi Y, Tani T, Oosaki H, Nanba T, Kozu R, Kotani T. Risk Factors of Patient-Related Safety Events during Active Mobilization for Intubated Patients in Intensive Care Units-A Multi-Center Retrospective Observational Study. J Clin Med. 2021;10(12):2607.

34. Nakamura K, Nakano H, Naraba H, Mochizuki M, Takahashi Y, Sonoo T, Hashimoto H, Abe T, Hayakawa M, Yamakawa K. Vasopressin Loading for Refractory Septic Shock: A Preliminary Analysis of a Case Series. Front Med (Lausanne). 2021;8:644195.

35. Sugiura A, Vogelhuber J, Öztürk C, Schwaibold Z, Reckers D, Goto T, Kavsur R, Becher MU, Zimmer S, Nickenig G, Weber M. PASCAL versus MitraClip-XTR edge-to-edge device for the treatment of tricuspid regurgitation: a propensity-matched analysis. Clin Res Cardiol. 2021;110(3):451-459

36. Nakamura K, Nakano H, Naraba H, Mochizuki M, Takahashi Y, Sonoo T, Hashimoto H, Morimura N. High protein versus medium protein delivery under equal total energy delivery in critical care: A randomized controlled trial. Clin Nutr. 2021;40(3):796-803.

37. Murakami H, Naraba H, Gondo T, Mochizuki M, Nakano H, Takahashi Y, Sonoo T, Hashimoto H, Nakamura K. Diagnostic Value of Serum Procalcitonin in Patients with Convulsion in Emergency Department, an Observational Study. Antibiotics (Basel). 2020;9(10):683.

38. Osawa I, Sato T, Goto T, Sonoo T, Iwai S, Nakajima S. Characteristics and subgroups of frequent emergency department users in an academic hospital in Japan. Acute Med Surg. 2020;7(1):e535

2023年

People's Award (most voted)
Team Leader: GOTO Tadahiro
"Development and Validation of a Bedside-Available Machine Learning Model to Predict Discrepancies between SaO2 and SpO2"
TMDU-NUS-MIT 3rd Critical Care Datathon

Finalists
Team Leader: Osawa Itsuki
"Heterogeneity in Treatment Effects of Lower Mechanical Power"
European Society of Intensive Care Medicine datathon

2022年

1st prize
Team Leader: GOTO Tadahiro
"Optimal hemodynamic management for preventing dialysis-requiring acute kidney injury in patients with sepsis using deep reinforcement learning"
European Society of Intensive Care Medicine datathon

2021年

Best Presentation Award in Datathon
Team Leader: GOTO Tadahiro
"Heterogeneity in treatment effects of hydrocortisone for sepsis to explore potential targets"
Healthcare AI EXPO 2021

2020年

Outstanding Performance Award in Datathon
Team Leader: GOTO Tadahiro
"The Contribution of Chest X-Ray to Predict Extubation Failure in Mechanically Ventilated Patients Using Machine Learning-Based Algorithms"
Healthcare AI EXPO 2020

2023

日本熱傷学会総会

1.（ランチョンセミナー）後藤匡啓：ビッグデータを用いた臨床研究：熱傷研究への応用とこれからの臨床研究

日本臨床救急医学会

1.（一般演題）時田亜希夫ら：救急外来に歩いて来院するくも膜下出血の特徴
2.（一般演題）後藤匡啓ら：救急隊から患者予後までの情報が繋がるデータベース構築とその利活用
3.（一般演題）後藤匡啓ら：救急隊向けモバイルアプリを用いた次世代の救急隊と病院との情報伝達

日本救急医学会総会　

1.（学生・研修医セッション）伊藤直毅ら：Descriptive Study on Patients Presenting with Posterior Neck Pain in the Emergency Department
2.（EMS-Asia Joint Session）後藤匡啓ら：救急外来受診患者の疫学的調査と類型分類に関する多施設観察研究（ECLIPSE-ED study）

日本臨床疫学会

1.（シンポジウム・座長・演者）後藤匡啓：臨床疫学における教師無し機械学習（クラスタリング）の使い方を徹底的に考える

日本集中治療医学会

1. （優秀演題）卯野木陽子ら：ICU再入室予測モデルの開発と妥当性の検証
2. （一般演題）埴岡紀和ら：動脈血液ガス分析（ABG）の必要性の予測する機械学習モデルの開発
3. （一般演題）門松咲南ら：脳卒中患者に対する気管挿管後の血圧上昇因子の分析

2022

European Society of Intensive Care Medicine Annual Meeting

1. （e-Poster）Fukuchi K, Osawa I, Shibata J, Goto T. Initiation timing of Hydrocortisone in Adults with Septic Shock: A Machine Learning-Based Approach to Estimate Time-Varying Treatment Effects.

2. （e-Poster）Shibata J, Osawa I, Fukuchi K, Goto T. The association between time from emergency department visit to ICU admission and mortality among patients with sepsis.

The 1st Joint Scientific Congress of TSCCM, TSECCM and JSICM

1. （Best Abstract Award）Fukaguchi K. Association of door to operation time with the prognosis in colorectal perforation.

日本集中治療医学会学術集会

1. （シンポジウム）中島幹男ら：ビッグデータとデータサイエンス. Japan Coma ScaleをGlasgow Coma Scaleへと換算する方法の開発と検証
2.（シンポジウム）福地清康ら：人工呼吸管理中の敗血症に対する深層強化学習を用いた鎮静薬の最適な投与戦略の構築
3. （一般演題）山田浩平ら：熱中症が疑われる患者の中から敗血症患者を同定し得る因子の探索:多施設観察研究
4. （一般演題）中村謙介ら：PIICS臨床診断基準における検査所見の機械学習による至適カットオフ解析
5. （一般演題）鱶口清満ら：大腸穿孔におけるDoor to Operation Timeと予後との関連

日本呼吸療法医学会学術集会

1. （一般演題）：上條泰ら：実体重または予測体重で調整したRSBIの抜管失敗に対する予測性能

日本救急医学会総会

1. （学生・研修医セッション）伊佐地里帆ら：市中肺炎の初期の重症度評価におけるA-DROPとCURB65の外的妥当性の検証
2. （学生・研修医セッション）柴田潤一郎ら：鈍的頸部血管症例における受傷起点,受傷パターンに関する記述研究
3. （学生・研修医セッション）柴田潤一郎ら：救急外来受診患者の病院前情報を用いた疾患群予測AIツールの開発

第25回 日本救急医学会中部地方会 総会・学術集会

1. （招待講演）後藤匡啓：救急医療における人工知能・機械学習の応用

2021

American College of Emergency Physician Scientific Assembly

1. Fujimori R et al. Acceptance and barriers of AI-based decision support systems in emergency departments: a quantitative and qualitative evaluation
2. Okuma A et al. Association between comorbid mental illness and preceding emergency department visits in unplanned admissions
3. Shibata J et al. Risk factors of sepsis among patients with qSOFA<2 in the emergency department
4. Ishizawa R et al. Characteristics of femoral fractures and accompanied fall-related injuries
5. Fukaguchi et al. The diagnostic accuracy of costovertebral angle tenderness in the emergency department

Society for Critical Care Medicine Annual Meeting

1. Fukuchi K, et al. Optimal Sedation Strategy for Ventilated Patients with Sepsis Using Deep Reinforcement Learning
2. Kamijo Y, et al. Predicting Extubation Failure Using Actual Body Weight-Adjusted Rapid Shallow Breathing Index
3. Yamada K, et al. Factors Differentiating Sepsis from Heatstroke in Patients with Suspected Heatstroke
4. Osawa I, et al. Machine Learning-Based Estimation of Potential Targets of Polymyxin-B Hemoperfusion Use for Sepsis
5. Shibata J, et al. Optimal Timing of Early Mobilization for ICU Patients with Sepsis: An IPW-Estimated Analysis

European Society of Intensive Care Medicine Annual Meeting

（International Sepsis Forum Award) Osawa I, et al. Targeted Antithrombin Use for Sepsis with Coagulopathy: A Machine Learning-Based Approach to Estimate Heterogeneous Treatment Effects

日本救急医学会総会

（教育講演）後藤匡啓：臨床研究とAIの融合、およびその応用を目指して
（優秀演題賞）齋藤朱花ら：敗血症予測におけるプレホスピタルと救急外来のqSOFAの有用性
（一般演題）柴田潤一郎ら：敗血症患者の救急外来受診時点におけるバイタルサインの類型と予後と の関連
（一般演題）添野祥子ら：救急外来受診時の脈圧と急性心血管イベントの関連
（一般演題）添野祥子ら：救急外来受診後30日以内に再受診した成人患者の特徴
（一般演題）元木麻衣子ら：NSERmobile導入による救急隊現場滞在時間への影響の検討
（一般演題）小倉健太郎ら：院外心停止患者におけるICU入室早期のモニター心電図波形を用いた予後予測
（一般演題）石澤嶺ら：転倒による大腿骨骨折に合併する外傷の検討

2020

Machine Learning for Healthcare

Hara K, Yoshihara R, Sonoo T, Shirakawa T, Goto T, Nakamura K. Development of phenotype algorithms for common acute conditions using SHapley Additive exPlanation values.

日本集中治療医学会学術集会

（シンポジウム）後藤匡啓：機械学習を用いたICUにおける臨床研究とその展望
（ワークショップ）劉啓文：新型コロナウイルス感染症患者におけるABCDEF bundle実施率・栄養療法の検討：学会主導前向き国際比較研究

1. 消防救急隊と搬送先病院の連携のための患者情報共有アプリ(NSER mobile)導入による病院前診療・救急医療体制への影響の検討、多機関共同研究（NEXT-INSPIRE study） に関するオプトアウト

2. 救急外来受診患者の疫学的調査と類型分類に関する多施設観察研究（ECLIPSE-ED study）のオプトアウト