AIMC Topic: Aged

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Established machine learning models to predict readmission for elderly patients with ischemic heart disease.

Kardiologia polska
BACKGROUND: The contribution of clinical features associated with 30-day or 1-year readmission in elderly patients with ischemic heart disease (IHD) and whether these features can be used to predict the readmission risk of patients has not been studi...

Ultrasound-based nomogram to predict the recurrence in papillary thyroid carcinoma using machine learning.

BMC cancer
BACKGROUND AND AIMS: The recurrence of papillary thyroid carcinoma (PTC) is not unusual and associated with risk of death. This study is aimed to construct a nomogram that combines clinicopathological characteristics and ultrasound radiomics signatur...

A powerful machine learning approach to identify interactions of differentially abundant gut microbial subsets in patients with metastatic and non-metastatic pancreatic cancer.

Gut microbes
Pancreatic cancer has a dismal prognosis, as it is often diagnosed at stage IV of the disease and is characterized by metastatic spread. Gut microbiota and its metabolites have been suggested to influence the metastatic spread by modulating the host ...

Machine Learning Based Prediction of Post-operative Infrarenal Endograft Apposition for Abdominal Aortic Aneurysms.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
OBJECTIVE: Challenging infrarenal aortic neck characteristics have been associated with an increased risk of type Ia endoleak after endovascular aneurysm repair (EVAR). Short apposition (< 10 mm circumferential shortest apposition length [SAL]) on th...

Traditional Methods Hold Their Ground Against Machine Learning in Predicting Potentially Inappropriate Medication Use in Older Adults.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Machine learning methods have gained much attention in health sciences for predicting various health outcomes but are scarcely used in pharmacoepidemiology. The ability to identify predictors of suboptimal medication use is essential for ...

Prediction of intra-abdominal injury using natural language processing of electronic medical record data.

Surgery
BACKGROUND: This study aimed to use natural language processing to predict the presence of intra-abdominal injury using unstructured data from electronic medical records.

Machine learning-based decision support model for selecting intra-arterial therapies for unresectable hepatocellular carcinoma: A national real-world evidence-based study.

British journal of cancer
IMPORTANCE: Intra-arterial therapies(IATs) are promising options for unresectable hepatocellular carcinoma(HCC). Stratifying the prognostic risk before administering IAT is important for clinical decision-making and for designing future clinical tria...

An artificial intelligence-driven support tool for prediction of urine culture test results.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND AND AIMS: We aimed to develop an easily deployable artificial intelligence (AI)-driven model for rapid prediction of urine culture test results.

Prediction of Freezing of Gait in Parkinson's disease based on multi-channel time-series neural network.

Artificial intelligence in medicine
Freezing of Gait (FOG) is a noticeable symptom of Parkinson's disease, like being stuck in place and increasing the risk of falls. The wearable multi-channel sensor system is an efficient method to predict and monitor the FOG, thus warning the wearer...