AIMC Topic: Vomiting

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Development and prospective evaluation of a machine learning model to predict vomiting among pediatric cancer and hematopoietic cell transplant patients.

BMC cancer
PURPOSE: Objectives were to develop a machine learning (ML) model based on electronic health record (EHR) data to predict the risk of vomiting within a 96-hour window after admission to the pediatric oncology and hematopoietic cell transplant (HCT) s...

Risk prediction model for chemotherapy-induced nausea and vomiting in cancer patients: a systematic review.

International journal of nursing studies
BACKGROUND: Chemotherapy-induced nausea and vomiting increase the healthcare burden and lead to adverse clinical outcomes in cancer patients. Although many risk prediction models for chemotherapy-induced nausea and vomiting have been developed, their...

A deep learning-based system for automatic detection of emesis with high accuracy in Suncus murinus.

Communications biology
Quantifying emesis in Suncus murinus (S. murinus) has traditionally relied on direct observation or reviewing recorded behaviour, which are laborious, time-consuming processes that are susceptible to operator error. With rapid advancements in deep le...

Anesthesia management experience for pediatric day-case PDA ligation under thoracoscopy assisted by a robot: a retrospective study.

Journal of cardiothoracic surgery
BACKGROUND: To summarize the anesthesia management experience for pediatric day-case patent ductus arteriosus (PDA) ligation under robot-assisted thoracoscopy and explore the key points of anesthesia management for this procedure.

A deep learning-based interpretable decision tool for predicting high risk of chemotherapy-induced nausea and vomiting in cancer patients prescribed highly emetogenic chemotherapy.

Cancer medicine
OBJECTIVE: This study aims to develop a risk prediction model for chemotherapy-induced nausea and vomiting (CINV) in cancer patients receiving highly emetogenic chemotherapy (HEC) and identify the variables that have the most significant impact on pr...

Vomiting Management and Effect Prediction after Early Chemotherapy of Lung Cancer with Diffusion-Weighted Imaging under Artificial Intelligence Algorithm and Comfort Care Intervention.

Computational and mathematical methods in medicine
This aim of this research was to explore the evaluation and prediction value of diffusion-weighted imaging (DWI) under artificial intelligence algorithm in the vomiting management and chemotherapy of early lung cancer under comfort care. 118 patients...

Identification of Uncontrolled Symptoms in Cancer Patients Using Natural Language Processing.

Journal of pain and symptom management
CONTEXT: For patients with cancer, uncontrolled pain and other symptoms are the leading cause of unplanned hospitalizations. Early access to specialty palliative care (PC) is effective to reduce symptom burden, but more efficient approaches are neede...

Real-time prediction of intradialytic relative blood volume: a proof-of-concept for integrated cloud computing infrastructure.

BMC nephrology
BACKGROUND: Inadequate refilling from extravascular compartments during hemodialysis can lead to intradialytic symptoms, such as hypotension, nausea, vomiting, and cramping/myalgia. Relative blood volume (RBV) plays an important role in adapting the ...

Machine learning prediction of emesis and gastrointestinal state in ferrets.

PloS one
Although electrogastrography (EGG) could be a critical tool in the diagnosis of patients with gastrointestinal (GI) disease, it remains under-utilized. The lack of spatial and temporal resolution using current EGG methods presents a significant roadb...