Deep learning continues to rapidly evolve and is now demonstrating remar...
Learning about diagnostic features and related clinical information from...
In the era of big data, there is an increasing need for healthcare provi...
Multiple Sclerosis (MS) is a chronic disease developed in human brain an...
Liver transplantation is a life-saving procedure for patients with end-s...
Organ transplant is the essential treatment method for some end-stage
di...
In this study, we investigated the potential of ChatGPT, a large languag...
Clinical trials are indispensable in developing new treatments, but they...
The process of matching patients with suitable clinical trials is essent...
Electronic health records (EHRs) store an extensive array of patient
inf...
Recent advancements in large language models (LLMs) have led to the
deve...
Liver transplant is an essential therapy performed for severe liver dise...
Social determinants of health (SDoH) have a significant impact on health...
Deep learning models trained on large-scale data have achieved encouragi...
As the sequencing costs are decreasing, there is great incentive to perf...
Tensor factorization has received increasing interest due to its intrins...
With the reduction of sequencing costs and the pervasiveness of computin...
Objectives: This paper develops two algorithms to achieve federated
gene...
Abstract:
Aim: The goal was to use a Deep Convolutional Neural Network...
The PC algorithm is the state-of-the-art algorithm for causal structure
...
In this work, we propose a novel problem formulation for de-identificati...
Our objective in this study is to investigate the behavior of Boolean
op...
Remote monitoring to support "aging in place" is an active area of resea...
Many COVID-19 patients developed prolonged symptoms after the infection,...
We propose a robust in-time predictor for in-hospital COVID-19 patient's...
Providing provenance in scientific workflows is essential for reproducib...
Distributed health data networks that use information from multiple sour...
Patient representation learning refers to learning a dense mathematical
...
Amid the pandemic of 2019 novel coronavirus disease (COVID-19) infected ...
Objective: We study the influence of local reopening policies on the
com...
Data integration and sharing maximally enhance the potential for novel a...
Tensor factorization has been demonstrated as an efficient approach for
...
In this paper, we studied the association between the change of structur...
Existing studies consider Alzheimer's disease (AD) a comorbidity of epil...
Sleep change is commonly reported in Alzheimer's disease (AD) patients a...
Acute kidney injury (AKI) in critically ill patients is associated with
...
Multi-task learning (MTL) refers to the paradigm of learning multiple re...
Secure computation of equivalence has fundamental application in many
di...
Tensor factorization models offer an effective approach to convert massi...
In many real-world applications of machine learning classifiers, it is
e...