Matthew M Churpek
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Explore the profile of Matthew M Churpek including associated specialties, affiliations and a list of published articles.
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155
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3411
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Recent Articles
1.
Ahmed K, Issaka S, Marcinak C, Virani S, Jaraczewski T, Afshar M, et al.
Ann Surg Oncol
. 2025 Feb;
PMID: 39979688
Background: Postdischarge venous thromboembolism (pdVTE) is a life-threatening complication following resection for pancreatic cancer (PC). While national guidelines recommend extended chemoprophylaxis for all, adherence is low and ranges from 1.5...
2.
Chokkara S, Hermsen M, Bonomo M, Kaskovich S, Hemmrich M, Carey K, et al.
Chronic Obstr Pulm Dis
. 2025 Jan;
PMID: 39874959
This study aimed to evaluate the performance of machine learning models for predicting readmission of patients with Chronic Obstructive Pulmonary Disease (COPD) based on administrative data and chart review data....
3.
Gao Y, Myers S, Chen S, Dligach D, Miller T, Bitterman D, et al.
JAMIA Open
. 2025 Jan;
8(1):ooae154.
PMID: 39802674
Objective: To evaluate large language models (LLMs) for pre-test diagnostic probability estimation and compare their uncertainty estimation performance with a traditional machine learning classifier. Materials And Methods: We assessed 2...
4.
Jawara D, Lauer K, Venkatesh M, Stalter L, Hanlon B, Churpek M, et al.
J Surg Res
. 2025 Jan;
306:43-53.
PMID: 39742657
Introduction: Obesity, defined as a body mass index ≥30 kg/m, is a major public health concern in the United States. Preventative approaches are essential, but they are limited by an...
5.
Myers S, Miller T, Gao Y, Churpek M, Mayampurath A, Dligach D, et al.
J Am Med Inform Assoc
. 2024 Dec;
32(2):357-364.
PMID: 39703187
Objectives: Applying large language models (LLMs) to the clinical domain is challenging due to the context-heavy nature of processing medical records. Retrieval-augmented generation (RAG) offers a solution by facilitating reasoning...
6.
Spicer A, Churpek M
Crit Care Med
. 2024 Dec;
53(1):e182-e185.
PMID: 39630950
No abstract available.
7.
Edelson D, Churpek M, Carey K, Lin Z, Huang C, Siner J, et al.
JAMA Netw Open
. 2024 Oct;
7(10):e2438986.
PMID: 39405061
Importance: Early warning decision support tools to identify clinical deterioration in the hospital are widely used, but there is little information on their comparative performance. Objective: To compare 3 proprietary...
8.
Buell K, Carey K, Dussault N, Parker W, Dumanian J, Bhavani S, et al.
Crit Care Explor
. 2024 Oct;
6(10):e1165.
PMID: 39392375
Background: Early diagnostic uncertainty for infection causes delays in antibiotic administration in infected patients and unnecessary antibiotic administration in noninfected patients. Objective: To develop a machine learning model for the...
9.
Bhavani S, Spicer A, Sinha P, Malik A, Lopez-Espina C, Schmalz L, et al.
Intensive Care Med
. 2024 Oct;
50(12):2094-2104.
PMID: 39382693
Purpose: Sepsis is a heterogeneous syndrome. Identification of sepsis subphenotypes with distinct immune profiles could lead to targeted therapies. This study investigates the immune profiles of patients with sepsis following...
10.
Churpek M, Ingebritsen R, Carey K, Rao S, Murnin E, Qyli T, et al.
Crit Care Explor
. 2024 Oct;
6(10):e1161.
PMID: 39356139
Importance: Timely intervention for clinically deteriorating ward patients requires that care teams accurately diagnose and treat their underlying medical conditions. However, the most common diagnoses leading to deterioration and the...