Randomized Trial of a Novel Artificial Intelligence/Machine Learning Model to Predict the Need for Specialty Palliative Care in Hospitalized Patients

被引：0

作者：

Strand, Jacod J. ^{[1
]}

Modgan, Alisha ^{[1
]}

Karow, Jordan ^{[1
]}

Olson, Emily ^{[1
]}

Wilson, Patrick ^{[1
]}

机构：

[1] Mayo Clin, Rochester, MN USA

来源：

JOURNAL OF PAIN AND SYMPTOM MANAGEMENT | 2023年 / 65卷 / 03期

关键词：

D O I：

暂无

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

FR205A

引用

页码：E274 / E274

页数：1

共 50 条

[21] A machine learning-based prognostic model to predict survival in patients with advanced cancer admitted to an acute palliative care unit
Jung, E. H.
Park, Y.
Kim, Y. J.
Yi, S.
Kim, K.
Oh, J.
Lee, S.
Kang, B.
Suh, K. J.
Lee, J. Y.
Kim, J-W.
Kim, S. H.
Kim, J. W.
Lee, J-O.
Lee, K-W.
Kim, J. H.
Bang, S-M.
Lee, J-S.
ANNALS OF ONCOLOGY, 2023, 34 : S891 - S891
[22] Development and validation of a machine learning model to predict venous thromboembolism among hospitalized cancer patients
Meng, Lingqi
Wei, Tao
Fan, Rongrong
Su, Haoze
Liu, Jiahui
Wang, Lijie
Huang, Xinjuan
Qi, Yi
Li, Xuying
ASIA-PACIFIC JOURNAL OF ONCOLOGY NURSING, 2022, 9 (12)
[23] Machine learning score to predict in-hospital outcomes in patients hospitalized in cardiac intensive care unit
Weizman, Orianne
Hamzi, Kenza
Henry, Patrick
Schurtz, Guillaume
Hauguel-Moreau, Marie
Trimaille, Antonin
Bedossa, Marc
Dib, Jean Claude
Attou, Sabir
Boukertouta, Tanissia
Boccara, Franck
Pommier, Thibaut
Lim, Pascal
Bochaton, Thomas
Millischer, Damien
Merat, Benoit
Picard, Fabien
Grinberg, Nissim
Sulman, David
Pasdeloup, Bastien
El Ouahidi, Yassine
Goncalves, Trecy
Vicaut, Eric
Dillinger, Jean-Guillaume
Toupin, Solenn
Pezel, Theo
ADDICT ICCU Investigators, Victor
EUROPEAN HEART JOURNAL - DIGITAL HEALTH, 2025, 6 (02): : 218 - 227
[24] NOVEL MACHINE LEARNING MODEL TO PREDICT NASH IN NAFLD PATIENTS WITH DIABETES MELLITUS
Aggarwal, Manik
Singh, Amandeep
Bansal, Agam
McCullough, Arthur J.
HEPATOLOGY, 2020, 72 : 932A - 933A
[25] Developing and evaluating a machine learning based algorithm to predict the need of pediatric intensive care unit transfer for newly hospitalized children
Zhai, Haijun
Brady, Patrick
Li, Qi
Lingren, Todd
Ni, Yizhao
Wheeler, Derek S.
Solti, Imre
RESUSCITATION, 2014, 85 (08) : 1065 - 1071
[26] Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model
Shao, Hui
Shi, Lizheng
Lin, Yilu
Fonseca, Vivian
JOURNAL OF DIABETES AND ITS COMPLICATIONS, 2022, 36 (11)
[27] A machine learning model to predict the need for conversion of operative approach in patients undergoing colectomy for neoplasm
Guidolin, Keegan
Ng, Deanna
Zorigtbaatar, Anudari
Chadi, Sami
Quereshy, Fayez
CANCER REPORTS, 2024, 7 (01)
[28] Multi- Site Randomized Trial of Inpatient Palliative Care for Hospitalized Patients Undergoing Hematopoietic Stem Cell Transplantation
El-Jawahri, Areej
LeBlanc, Thomas W.
Kavanaugh, Alison
Webb, Jason
Fausto, James
Traeger, Lara
Greer, Joseph
Jackson, Vicki
Horick, Nora
Defilipp, Zachariah
Chen, Yi-Bin
Lee, Stephanie J.
Temel, Jennifer
BLOOD, 2023, 142
[29] Explainable Machine Learning Model to Predict Overall Survival in Patients Treated With Palliative Radiotherapy for Bone Metastases
Cilla, Savino
Rossi, Romina
Habberstad, Ragnhild
Klepstad, Pal
Dall'Agata, Monia
Kaasa, Stein
Valenti, Vanessa
Donati, Costanza M.
Maltoni, Marco
Morganti, Alessio G.
JCO CLINICAL CANCER INFORMATICS, 2024, 8 : e2400027
[30] DEVELOPMENT AND EXTERNAL VALIDATION OF A MACHINE LEARNING MODEL TO PREDICT BILEVEL NONINVASIVE VENTILATION FAILURE IN HOSPITALIZED PATIENTS
Temte, Brandon
Carey, Kyle a
Shah, Nirav s
Winslow, Christopher
Gilbert, Emily r
Afshar, Majid
Edelson, Dana p
Churpek, Matthew m
CHEST, 2024, 166 (04) : A1741 - A1741

← 1 2 3 4 5 →