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Venet Osmani

Explore the profile of Venet Osmani including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 32
Citations 510
Followers 0
Related Specialties
Medical Informatics
General Medicine
Biomedical Engineering
Top 10 Co-Authors
Behrooz Mamandipoor
Bernhard Wernly
Christian Jung
Raphael Romano Bruno
Richard Rezar
Malte Kelm
Dylan W de Lange
Sarah Wernly
Seyedmostafa Sheikhalishahi
Oscar Mayora
Published In
Annu Int Conf IEEE Eng Med Biol Soc
JMIR Med Inform
PLoS One
IEEE J Biomed Health Inform
BMC Med Inform Decis Mak
Affiliations
Soon will be listed here.
Recent Articles
1.
Artificial intelligence of imaging and clinical neurological data for predictive, preventive and personalized (P3) medicine for Parkinson Disease: The NeuroArtP3 protocol for a multi-center research study
Malaguti M, Gios L, Giometto B, Longo C, Riello M, Ottaviani D, et al.
PLoS One . 2024 Mar; 19(3):e0300127. PMID: 38483951
Background: The burden of Parkinson Disease (PD) represents a key public health issue and it is essential to develop innovative and cost-effective approaches to promote sustainable diagnostic and therapeutic interventions....
2.
An interpretable deep learning model for time-series electronic health records: Case study of delirium prediction in critical care
Sheikhalishahi S, Bhattacharyya A, Celi L, Osmani V
Artif Intell Med . 2023 Oct; 144:102659. PMID: 37783541
Deep Learning (DL) models have received increasing attention in the clinical setting, particularly in intensive care units (ICU). In this context, the interpretability of the outcomes estimated by the DL...
3.
Machine learning models predict liver steatosis but not liver fibrosis in a prospective cohort study
Mamandipoor B, Wernly S, Semmler G, Flamm M, Jung C, Aigner E, et al.
Clin Res Hepatol Gastroenterol . 2023 Jul; 47(7):102181. PMID: 37467893
Introduction: Screening for liver fibrosis continues to rely on laboratory panels and non-invasive tests such as FIB-4-score and transient elastography. In this study, we evaluated the potential of machine learning...
4.
The impact of ethnic background on ICU care and outcome in sepsis and septic shock - A retrospective multicenter analysis on 17,949 patients
Kokofer A, Mamandipoor B, Flamm M, Rezar R, Wernly S, Datz C, et al.
BMC Infect Dis . 2023 Apr; 23(1):194. PMID: 37003970
Background: Previous studies have been inconclusive about racial disparities in sepsis. This study evaluated the impact of ethnic background on management and outcome in sepsis and septic shock. Methods: This...
5.
COVID-19 machine learning model predicts outcomes in older patients from various European countries, between pandemic waves, and in a cohort of Asian, African, and American patients
Mamandipoor B, Bruno R, Wernly B, Wolff G, Fjolner J, Artigas A, et al.
PLOS Digit Health . 2023 Feb; 1(11):e0000136. PMID: 36812571
Background: COVID-19 remains a complex disease in terms of its trajectory and the diversity of outcomes rendering disease management and clinical resource allocation challenging. Varying symptomatology in older patients as...
6.
Hyperlactatemia and altered lactate kinetics are associated with excess mortality in sepsis : A multicenter retrospective observational study
Rezar R, Mamandipoor B, Seelmaier C, Jung C, Lichtenauer M, Hoppe U, et al.
Wien Klin Wochenschr . 2022 Dec; 135(3-4):80-88. PMID: 36576554
Severe hyperlactatemia (>10mmol/L) or impaired lactate metabolism are known to correlate with increased mortality. The maximum lactate concentration on day 1 of 10,724 septic patients from the eICU Collaborative Research...
7.
Automatically detecting Crohn's disease and Ulcerative Colitis from endoscopic imaging
Chierici M, Puica N, Pozzi M, Capistrano A, Dorian Donzella M, Colangelo A, et al.
BMC Med Inform Decis Mak . 2022 Nov; 22(Suppl 6):300. PMID: 36401328
Background: The SI-CURA project (Soluzioni Innovative per la gestione del paziente e il follow up terapeutico della Colite UlceRosA) is an Italian initiative aimed at the development of artificial intelligence...
8.
Delirium prediction in the ICU: designing a screening tool for preventive interventions
Bhattacharyya A, Sheikhalishahi S, Torbic H, Yeung W, Wang T, Birst J, et al.
JAMIA Open . 2022 Jun; 5(2):ooac048. PMID: 35702626
Introduction: Delirium occurrence is common and preventive strategies are resource intensive. Screening tools can prioritize patients at risk. Using machine learning, we can capture time and treatment effects that pose...
9.
Management of intoxicated patients - a descriptive outcome analysis of 4,267 ICU patients
Rezar R, Jung C, Mamandipoor B, Seelmaier C, Felder T, Lichtenauer M, et al.
BMC Emerg Med . 2022 Mar; 22(1):38. PMID: 35279068
Introduction: Intoxications are common in intensive care units (ICUs). The number of causative substances is large, mortality usually low. This retrospective cohort study aims to characterize differences of intoxicated compared...
10.
Disease-Course Adapting Machine Learning Prognostication Models in Elderly Patients Critically Ill With COVID-19: Multicenter Cohort Study With External Validation
Jung C, Mamandipoor B, Fjolner J, Bruno R, Wernly B, Artigas A, et al.
JMIR Med Inform . 2022 Jan; 10(3):e32949. PMID: 35099394
Background: The COVID-19 pandemic caused by SARS-CoV-2 is challenging health care systems globally. The disease disproportionately affects the elderly population, both in terms of disease severity and mortality risk. Objective:...