相关论文: iCardo: A Machine Learning Based Smart Healthcare …
Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, accounting for over 30% of global deaths according to the World Health Organization (WHO). Importantly, one-third of these deaths are preventable with timely and…
Cerebrovascular diseases (CVD) can lead to stroke and dementia. Stroke is the second leading cause of death world wide and dementia incidence is increasing by the year. There are several markers of CVD that are visible on brain imaging,…
This study provides an overview of heart disease prediction using an intelligent system. Predicting disease accurately is crucial in the medical field, but traditional methods relying solely on a doctor's experience often lack precision. To…
Accurate diagnosis is required before performing proper treatments for coronary heart disease. Machine learning based approaches have been proposed by many researchers to improve the accuracy of coronary heart disease diagnosis. Ensemble…
Current clinical practice guidelines for managing Coronary Artery Disease (CAD) account for general cardiovascular risk factors. However, they do not present a framework that considers personalized patient-specific characteristics. Using…
The alarmingly high mortality rate and increasing global prevalence of cardiovascular diseases signify the crucial need for early detection schemes. Phonocardiogram (PCG) signals have been historically applied in this domain owing to its…
Cardiovascular magnetic resonance (CMR) is the gold standard for assessing cardiac function, but individual cardiac cycles complicate automatic temporal comparison or sub-phase analysis. Accurate cardiac keyframe detection can eliminate…
Cardio/cerebrovascular diseases (CVD) have become one of the major health issue in our societies. But recent studies show that the present pathology tests to detect CVD are ineffectual as they do not consider different stages of platelet…
Recent advancements in Artificial Intelligence (AI) have significantly influenced the field of Cardiovascular Disease (CVD) analysis, particularly in image-based diagnostics. Our paper presents an extensive review of AI applications in…
Cardiovascular disease (CVD) is a major pediatric health burden, and early screening is of critical importance. Electrocardiography (ECG), as a noninvasive and accessible tool, is well suited for this purpose. This paper presents the first…
As the global population ages, the incidence of Chronic Kidney Disease (CKD) is rising. CKD often remains asymptomatic until advanced stages, which significantly burdens both the healthcare system and patient quality of life. This research…
Traditionally, medical discoveries are made by observing associations and then designing experiments to test these hypotheses. However, observing and quantifying associations in images can be difficult because of the wide variety of…
Cardiovascular diseases (CVD) are a predominant health concern globally, emphasizing the need for advanced diagnostic techniques. In our research, we present an avant-garde methodology that synergistically integrates ECG readings and…
While deep-learning based recommender systems utilizing collaborative filtering have been commonly used for recommendation in other domains, their application in the medical domain have been limited. In addition to modeling user-item…
Most people around the globe are dying due to heart disease. The main reason behind the rapid increase in the death rate due to heart disease is that there is no infrastructure developed for the healthcare department that can provide a…
As the number of patients with heart failure increases, machine learning (ML) has garnered attention in cardiomyopathy diagnosis, driven by the shortage of pathologists. However, endomyocardial biopsy specimens are often small sample size…
Automated noninvasive cardiac diagnosis plays a critical role in the early detection of cardiac disorders and cost-effective clinical management. Automated diagnosis involves the automated segmentation and analysis of cardiac images.…
Cardiovascular disease (CVD) is a leading cause of death globally, necessitating precise forecasting models for monitoring vital signs like heart rate, blood pressure, and ECG. Traditional models, such as ARIMA and Prophet, are limited by…
Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, underscoring the need for reliable and efficient predictive tools that support early intervention. Traditional diagnostic approaches rely on handcrafted features…
Machine Learning applications have brought new insights into a secondary analysis of medical data. Machine Learning helps to develop new drugs, define populations susceptible to certain illnesses, identify predictors of many common…