AIMC Topic: Risk Factors

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Risk factors of recurrence after robot-assisted laparoscopic partial nephrectomy for solitary localized renal cell carcinoma.

Scientific reports
To evaluate the recurrence rate and risk factors of recurrence after robot-assisted laparoscopic partial nephrectomy for solitary renal cell carcinoma (RCC). A total of 1265 cases of initial solitary localized RCC were analyzed. The baseline characte...

A stroke prediction framework using explainable ensemble learning.

Computer methods in biomechanics and biomedical engineering
The death of brain cells occurs when blood flow to a particular area of the brain is abruptly cut off, resulting in a stroke. Early recognition of stroke symptoms is essential to prevent strokes and promote a healthy lifestyle. FAST tests (looking fo...

INTERPRETABLE MACHINE LEARNING FOR PREDICTING RISK OF INVASIVE FUNGAL INFECTION IN CRITICALLY ILL PATIENTS IN THE INTENSIVE CARE UNIT: A RETROSPECTIVE COHORT STUDY BASED ON MIMIC-IV DATABASE.

Shock (Augusta, Ga.)
The delayed diagnosis of invasive fungal infection (IFI) is highly correlated with poor prognosis in patients. Early identification of high-risk patients with invasive fungal infections and timely implementation of targeted measures is beneficial for...

hART: Deep learning-informed lifespan heart failure risk trajectories.

International journal of medical informatics
BACKGROUND: Heart failure (HF) results in persistent risk and long-term comorbidities. This is particularly true for patients with lifelong HF sequelae of cardiovascular disease such as patients with congenital heart disease (CHD).

Prediction of pregnancy-related complications in women undergoing assisted reproduction, using machine learning methods.

Fertility and sterility
OBJECTIVE: To use machine learning methods to develop prediction models of pregnancy complications in women who conceived with assisted reproductive techniques (ART).

Establishment of a machine learning predictive model for non-alcoholic fatty liver disease: A longitudinal cohort study.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease, which lacks effective drug treatments. This study aimed to construct an eXtreme Gradient Boosting (XGBoost) prediction model to identify or evaluate pot...

Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.

BMC medical informatics and decision making
Timely and accurate referral of end-stage heart failure patients for advanced therapies, including heart transplants and mechanical circulatory support, plays an important role in improving patient outcomes and saving costs. However, the decision-mak...

Predicting suicide risk in real-time crisis hotline chats integrating machine learning with psychological factors: Exploring the black box.

Suicide & life-threatening behavior
BACKGROUND: This study addresses the suicide risk predicting challenge by exploring the predictive ability of machine learning (ML) models integrated with theory-driven psychological risk factors in real-time crisis hotline chats. More importantly, w...

Acute Kidney Injury in Acute Myocardial Infarction and Its Outcome at 3 and 6 Months.

Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Epidemiological data on the prevalence of acute kidney injury (AKI) in acute coronary syndrome are sparse, with most studies having been conducted retrospectively. This study prospectively analyzed the incidence of AKI in patients with acute myocardi...