A5012478940- Artificial Intelligence in Healthcare
- Machine Learning in Healthcare
- Traditional Chinese Medicine Studies
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Diabetes Management and Research
- Context-Aware Activity Recognition Systems
- Healthcare Technology and Patient Monitoring
- Face recognition and analysis
- Retinal Imaging and Analysis
- Computational Drug Discovery Methods
- Statistical Methods and Inference
- Cellular Mechanics and Interactions
- Cardiovascular Health and Disease Prevention
- Sepsis Diagnosis and Treatment
- Human Mobility and Location-Based Analysis
- Flexible and Reconfigurable Manufacturing Systems
- Health, Environment, Cognitive Aging
- Electronic Health Records Systems
- Elasticity and Material Modeling
- Diabetes Treatment and Management
- Nutritional Studies and Diet
- Retinal Diseases and Treatments
- Tendon Structure and Treatment
- Machine Learning in Materials Science
- Intensive Care Unit Cognitive Disorders
Marche Polytechnic University
2016-2023
ORCID
2021
The diagnosis of type 2 diabetes (T2D) at an early stage has a key role for adequate T2D integrated management system and patient's follow-up. Recent years have witnessed increasing amount available electronic health record (EHR) data machine learning (ML) techniques been considerably evolving. However, managing modeling this information may lead to several challenges, such as overfitting, model interpretability, computational cost. Starting from these motivations, we introduced ML method...
Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest the development prediction models as they excel in analysis complex signals data-rich environments such critical care.We retrieved data on COVID-19 admitted to an intensive care unit (ICU) between March...
Kidney Disease (KD) may hide complex causes and is associated with a tremendous socio-economic impact. Timely identification management from the first level of medical care represent most effective strategy to address growing global burden sustainably. Clinical practice guidelines suggest utilizing estimated Glomerular Filtration Rate (eGFR) for routine evaluation within screening purpose. Accordingly, analysis Electronic Health Records (EHRs) using Machine Learning techniques offers great...
The missing data mechanism is a relevant problem in Machine Learning (ML) and biomedical informatics communities. Real-world Electronic Health Record (EHR) datasets comprise several values, thus revealing high level of spatiotemporal sparsity the predictors' matrix. Several approaches state-of-the-art tried to deal with this by proposing different imputation strategies that (i) are often unrelated ML model, (ii) not conceived for EHR where laboratory exams prescribed uniformly over time...
Objective Decision support systems (DSS) have been developed and promoted for their potential to improve quality of health care. However, there is a lack common clinical strategy poor management resources erroneous implementation preventive medicine. Methods To overcome this problem, work proposed an integrated system that relies on the creation sharing database extracted from GPs' Electronic Health Records (EHRs) within Netmedica Italian (NMI) cloud infrastructure. Although pilot...
Diabetic Retinopathy (DR) is the most common and insidious microvascular complication of diabetes, can progress asymptomatically until a sudden loss vision occurs. Although DR prevalent nowadays, its prevention remains challenging. The multiple aim this study was to predict risk developing as diabetic (task 1) and, subsequently, temporally stratify 2) using electronic health records data. To perform these objectives, novel preprocessing procedure designed select both control pathological...
Earlier diagnosis plays a pivotal role in clinical applications, since it can strongly reduce the incidence and impact of many diseases and, consequently, reduction health care costs. This last aspect depends from right therapy prescriptions, especially when there are various opportunities. Within this context, Clinical Decision Support Systems (CDSS) could bring several benefits. In paper, we propose CDSS with aim improving clinician practice based on recommendations, assessment patient...
Endothelial Dysfunction is achieving increasing importance, because it strictly related to cardiovascular risks and provides important prognostic data in addition the classical ones. This paper introduces a machine learning approach for predicting Dysfunction. The was applied tested on newly collected dataset, "Endothelial Dataset (EDD)" several algorithms are compared. method comprises features anthropometric or pathological characteristics of analysed subjects. experiments yield high...
The estimation of Biological Age (BA) has been debated for several years and no clear universal understanding yet reached to solve this task. Accordingly, the knowledge an accurate BA index each individual may be relevant in various areas including health, economy, social policies decision making processes. main contribution work is design a Machine Learning based-consumer healthcare platform powered by electronic health record data (clinical features) smartphone (lifestyle order estimate...
In literature a standard protocol to develop an automatic procedure mechanically characterize soft tissue material does not exist yet. in this paper we propose that permits automatically calculate the Young's modulus and Poisson ratio for characterized during uniaxial tensile test. The experimental setup requires use of several markers camera obtaining true stress strain curve under fact, post processing image analysis measure real displacement tracking movement mean width variation specimen...
Abstract The Comet Assay is a well-known procedure employed to investigate the DNA damage and can be applied several research areas such as environmental, medical health sciences. User dependency computation time effort represent some of major drawbacks Assay. Starting from this motivation, we Machine Learning (ML) tool for discriminating using standard hand-crafted feature set. experimental results demonstrate how ML able objectively replicate human experts scoring (accuracy detection up...
Abstract Intensive medical attention of preterm babies is crucial to avoid short-term and long-term complications. Within neonatal intensive care units (NICUs), cribs are equipped with electronic devices aimed at: monitoring, administering drugs supporting clinician in making diagnosis offer treatments. To manage this huge data flux, a cloud-based healthcare infrastructure that allows collection from different (i.e., patient monitors, bilirubinometers, transcutaneous bilirubinometers),...