Martina Vettoretti

2.6k total citations · 1 hit paper
60 papers, 1.7k citations indexed

About

Martina Vettoretti is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Genetics. According to data from OpenAlex, Martina Vettoretti has authored 60 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Endocrinology, Diabetes and Metabolism, 33 papers in Surgery and 25 papers in Genetics. Recurrent topics in Martina Vettoretti's work include Diabetes Management and Research (43 papers), Pancreatic function and diabetes (32 papers) and Diabetes and associated disorders (25 papers). Martina Vettoretti is often cited by papers focused on Diabetes Management and Research (43 papers), Pancreatic function and diabetes (32 papers) and Diabetes and associated disorders (25 papers). Martina Vettoretti collaborates with scholars based in Italy, United Kingdom and Austria. Martina Vettoretti's co-authors include Andrea Facchinetti, Giovanni Sparacino, Giacomo Cappon, Giada Acciaroli, Claudio Cobelli, Barbara Di Camillo, Simone Del Favero, Enrico Longato, R. Visentin and Michele Schiavon and has published in prestigious journals such as PLoS ONE, Diabetes Care and Diabetes.

In The Last Decade

Martina Vettoretti

55 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications

2019 289 citations Giacomo Cappon, Martina Vettoretti et al. profile →

Peers

Countries citing papers authored by Martina Vettoretti

Since Specialization

Citations

This map shows the geographic impact of Martina Vettoretti's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Martina Vettoretti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martina Vettoretti more than expected).

Fields of papers citing papers by Martina Vettoretti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martina Vettoretti. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Martina Vettoretti. The network helps show where Martina Vettoretti may publish in the future.

Co-authorship network of co-authors of Martina Vettoretti

This figure shows the co-authorship network connecting the top 25 collaborators of Martina Vettoretti. A scholar is included among the top collaborators of Martina Vettoretti based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Martina Vettoretti. Martina Vettoretti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	AirPredict: an eHealth platform for asthma management leveraging wearable sensors, digital diaries, and air quality monitoring to optimize patient outcomes 2025 ·Frontiers in Digital Health ·(unknown), (unknown), (unknown), Giacomo Cappon, Mariaenrica Tinè, (unknown), (unknown), Simonetta Baraldo, Umberto Semenzato, Martina Vettoretti	1
2	A machine learning framework for short-term prediction of chronic obstructive pulmonary disease exacerbations using personal air quality monitors and lifestyle data 2025 ·Scientific Reports ·Mattia Atzeni, Giacomo Cappon, Jennifer K Quint, Frank J. Kelly, Benjamin Barratt, Martina Vettoretti	2
3	Predicting clinical events characterizing the progression of amyotrophic lateral sclerosis via machine learning approaches using routine visits data: a feasibility study 2024 ·BMC Medical Informatics and Decision Making ·(unknown), (unknown), (unknown), (unknown), Erica Tavazzi, Enrico Longato, Umberto Manera, Adriano Chiò, Marta Gromicho, (unknown), Mamede de Carvalho, Martina Vettoretti, Barbara Di Camillo	2
4	DYNAMITE: Integrating Archetypal Analysis and Process Mining for Interpretable Disease Progression Modelling 2024 ·IEEE Journal of Biomedical and Health Informatics ·(unknown), Erica Tavazzi, Martina Vettoretti, Roberto Gatta, Rosario Vasta, Adriano Chiò, Barbara Di Camillo	2
5	Risk of hypoglycemia in type 1 diabetes management: An in-silico sensitivity analysis to assess and rank the quantitative impact of different behavioral factors 2023 ·Computer Methods and Programs in Biomedicine ·(unknown), (unknown), Martina Vettoretti, Andrea Facchinetti, Pratik Choudhary, Giovanni Sparacino, Simone Del Favero	0
6	Generation of post-meal insulin correction boluses in type 1 diabetes simulation models for in-silico clinical trials: More realistic scenarios obtained using a decision tree approach 2022 ·Computer Methods and Programs in Biomedicine ·(unknown), Martina Vettoretti, Simone Del Favero, Antonella Facchinetti, Pratik Choudhary, Giovanni Sparacino	4
7	Implantable and transcutaneous continuous glucose monitoring system: a randomized cross over trial comparing accuracy, efficacy and acceptance 2021 ·Journal of Endocrinological Investigation ·Federico Boscari, Martina Vettoretti, Francesco Cavallin, (unknown), (unknown), (unknown), Angelo Avogaro, Andrea Facchinetti, Daniela Bruttomesso	13
8	Design of clinical trials to assess diabetes treatment: Minimum duration of continuous glucose monitoring data to estimate time‐in‐ranges with the desired precision 2021 ·Diabetes Obesity and Metabolism ·(unknown), Martina Vettoretti, Giovanni Sparacino, Andrea Facchinetti, Julia K. Mader, Pratik Choudhary, Simone Del Favero	8
9	Forecasting of Glucose Levels and Hypoglycemic Events: Head-to-Head Comparison of Linear and Nonlinear Data-Driven Algorithms Based on Continuous Glucose Monitoring Data Only 2021 ·Sensors ·(unknown), Simone Del Favero, Martina Vettoretti, Giovanni Sparacino, Andrea Facchinetti	46
10	Machine-Learning Based Model to Improve Insulin Bolus Calculation in Type 1 Diabetes Therapy 2020 ·IEEE Transactions on Biomedical Engineering ·Giulia Noaro, Giacomo Cappon, Martina Vettoretti, Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti	35
11	Modeling Carbohydrate Counting Error in Type 1 Diabetes Management 2020 ·Diabetes Technology & Therapeutics ·(unknown), Martina Vettoretti, Simone Del Favero, Andrea Facchinetti, Giovanni Sparacino	29
12	An analytical approach to determine the optimal duration of continuous glucose monitoring data required to reliably estimate time in hypoglycemia 2020 ·Scientific Reports ·(unknown), Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino, Julia K. Mader, Pratik Choudhary, Simone Del Favero	10
13	877-P: Limits of Correlation Coefficient Analysis in Determining the Minimal Duration of CGM Data Needed to Estimate Time Below Range 2020 ·Diabetes ·(unknown), Martina Vettoretti, (unknown), Andrea Facchinetti, (unknown), Julia K. Mader, Pratik Choudhary, Simone Del Favero	4
14	Comparing the accuracy of transcutaneous sensor and 90-day implantable glucose sensor 2020 ·Nutrition Metabolism and Cardiovascular Diseases ·Federico Boscari, Martina Vettoretti, (unknown), (unknown), (unknown), Elisabetta Iori, Angelo Avogaro, Andrea Facchinetti, Daniela Bruttomesso	7
15	Modeling the error of factory-calibrated continuous glucose monitoring sensors: application to Dexcom G6 sensor data 2019 ·PubMed ·Martina Vettoretti, Simone Del Favero, Giovanni Sparacino, Andrea Facchinetti	9
16	A Real-Time Continuous Glucose Monitoring–Based Algorithm to Trigger Hypotreatments to Prevent/Mitigate Hypoglycemic Events 2019 ·Diabetes Technology & Therapeutics ·(unknown), Martina Vettoretti, Simone Del Favero, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti	17
17	Combining continuous glucose monitoring and insulin pumps to automatically tune the basal insulin infusion in diabetes therapy: a review 2019 ·BioMedical Engineering OnLine ·Martina Vettoretti, Andrea Facchinetti	32
18	Importance of Recalibrating Models for Type 2 Diabetes Onset Prediction: Application of the Diabetes Population Risk Tool on the Health and Retirement Study 2018 ·PubMed ·Martina Vettoretti, Enrico Longato, Barbara Di Camillo, Andrea Facchinetti	4
19	Personalized blood glucose prediction: A hybrid approach using grammatical evolution and physiological models 2017 ·PLoS ONE ·Iván Contreras, Silvia Oviedo, Martina Vettoretti, R. Visentin, Josep Vehı́	58
20	Toward Calibration-Free Continuous Glucose Monitoring Sensors: Bayesian Calibration Approach Applied to Next-Generation Dexcom Technology 2017 ·Diabetes Technology & Therapeutics ·Giada Acciaroli, Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino	15

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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