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Matteo Danieletto
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Machine learning to predict mortality and critical events in a cohort of patients with COVID-19 in New York City: model development and validation
A Vaid, S Somani, AJ Russak, JK De Freitas, FF Chaudhry, I Paranjpe, ...
Journal of medical Internet research 22 (11), e24018, 2020
1262020
Clinical characteristics of hospitalized Covid-19 patients in New York City
I Paranjpe, AJ Russak, JK De Freitas, A Lala, R Miotto, A Vaid, ...
MedRxiv, 2020.04. 19.20062117, 2020
1152020
Acute kidney injury in hospitalized patients with COVID-19
L Chan, K Chaudhary, A Saha, K Chauhan, A Vaid, M Baweja, ...
MedRxiv, 2020.05. 04.20090944, 2020
1052020
Deep representation learning of electronic health records to unlock patient stratification at scale
I Landi, BS Glicksberg, HC Lee, S Cherng, G Landi, M Danieletto, ...
NPJ digital medicine 3 (1), 96, 2020
802020
Use of physiological data from a wearable device to identify SARS-CoV-2 infection and symptoms and predict COVID-19 diagnosis: observational study
RP Hirten, M Danieletto, L Tomalin, KH Choi, M Zweig, E Golden, S Kaur, ...
Journal of medical Internet research 23 (2), e26107, 2021
702021
Anti-spoofing and open GNSS signal authentication with signal authentication sequences
O Pozzobon, L Canzian, M Danieletto, A Dalla Chiara
2010 5th ESA Workshop on Satellite Navigation Technologies and European …, 2010
492010
Reflecting health: smart mirrors for personalized medicine
R Miotto, M Danieletto, JR Scelza, BA Kidd, JT Dudley
NPJ digital medicine 1 (1), 62, 2018
322018
Machine learning to predict mortality and critical events in covid-19 positive new york city patients
A Vaid, S Somani, AJ Russak, JK De Freitas, FF Chaudhry, I Paranjpe, ...
medRxiv, 2020.04. 26.20073411, 2020
272020
Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City
I Paranjpe, AJ Russak, JK De Freitas, A Lala, R Miotto, A Vaid, ...
BMJ open 10 (11), e040736, 2020
242020
Autonomous discovery, localization and recognition of smart objects through WSN and image features
E Menegatti, M Danieletto, M Mina, A Pretto, A Bardella, S Zanconato, ...
2010 IEEE Globecom Workshops, 1653-1657, 2010
242010
RAZOR: A compression and classification solution for the internet of things
M Danieletto, N Bui, M Zorzi
Sensors 14 (1), 68-94, 2013
232013
Machine learning to predict mortality and critical events in COVID-19 positive New York city patients: a cohort study
A Vaid, S Somani, AJ Russak, JK De Freitas, FF Chaudhry, I Paranjpe, ...
J. Med. Internet Res 22 (11), 2020
192020
CARMEN: a cognitive networking testbed on android OS devices
M Danieletto, G Quer, RR Rao, M Zorzi
IEEE Communications Magazine 52 (9), 98-107, 2014
192014
A resilience-building app to support the mental health of health care workers in the COVID-19 era: design process, distribution, and evaluation
EA Golden, M Zweig, M Danieletto, K Landell, G Nadkarni, E Bottinger, ...
JMIR Formative Research 5 (5), e26590, 2021
182021
Satellite images and machine learning can identify remote communities to facilitate access to health services
PS Emilie Bruzelius, Matthew Le, Avi Kenny, Jordan Downey, Matteo Danieletto ...
Journal of the American Medical Informatics Association 26 (8-9), 806-812, 2019
162019
Estimating the number of receiving nodes in 802.11 networks via machine learning techniques
D Del Testa, M Danieletto, GM Di Nunzio, M Zorzi
2016 IEEE Global Communications Conference (GLOBECOM), 1-7, 2016
152016
Longitudinal autonomic nervous system measures correlate with stress and ulcerative colitis disease activity and predict flare
RP Hirten, M Danieletto, R Scheel, M Shervey, J Ji, L Hu, J Sauk, L Chang, ...
Inflammatory bowel diseases 27 (10), 1576-1584, 2021
142021
Processing of electronic health records using deep learning: a review
V Osmani, L Li, M Danieletto, B Glicksberg, J Dudley, O Mayora
arXiv preprint arXiv:1804.01758, 2018
132018
Improving internet of things communications through compression and classification
M Danieletto, N Bui, M Zorzi
2012 IEEE International Conference on Pervasive Computing and Communications …, 2012
132012
Scaling structural learning with NO-BEARS to infer causal transcriptome networks
HC Lee, M Danieletto, R Miotto, ST Cherng, JT Dudley
PACIFIC SYMPOSIUM ON BIOCOMPUTING 2020, 391-402, 2019
122019
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