Precision Medicine Using Artificial Intelligence To Stratify Disease Severity In Patients With [...] Lazio

Precision Medicine Using Artificial Intelligence To Stratify Disease Severity In Patients With [...]
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Organisation/Company: Università degli Studi di Torino Research Field: Medical sciences Researcher Profile: Recognised Researcher (R2), Leading Researcher (R4), First Stage Researcher (R1), Established Researcher (R3) Country: Italy Application Deadline: 27 Jan 2025 - 13:00 (UTC) Type of Contract: To be defined Job Status: Not Applicable Is the job funded through the EU Research Framework Programme?

Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure?

No Offer Description NAFLD is currently the most common liver disease, but prognosis prediction is very difficult.

Liver fibrosis is the main determinant of prognosis.

The lack of robust and widely applicable non-invasive methods for risk stratification and prognostication of liver-related morbidity and mortality is a key hurdle hampering effective clinical management.

The project will develop novel algorithms enabling: Risk stratification of liver fibrosis Prediction of liver-related events Identification of patient sub-groups with different prognosis The project builds up on a large cohort with histologically diagnosed NAFLD and a well-characterized dataset of clinical, biochemical, anthropometric variables, and imaging data.

By exploiting artificial intelligence, we will develop accurate non-invasive algorithms for disease risk stratification and prediction of hepatic morbidity/mortality.

Eligibility of fellows: country/ies of residence: All Eligibility of fellows: nationality/ies: #J-18808-Ljbffr