Skip to main content
European Commission logo print header

Mathematical Optimization for clinical DEcision Support and Training

Descrizione del progetto

Migliorare il processo decisionale in ambito clinico mediante l’ottimizzazione matematica

I medici hanno la costante responsabilità di prendere decisioni cruciali nel loro lavoro quotidiano in un’ampia gamma di ambiti, dalla programmazione degli appuntamenti alla determinazione dei dosaggi ottimali per i trattamenti chemioterapici. La base di queste decisioni è una combinazione di conoscenze ed esperienze acquisite dal medico. Tuttavia, la sfida sta nel fatto che questa preziosa esperienza non è facilmente trasferibile o accessibile. Il progetto MODEST, finanziato dal CER, intende fornire ai medici un sistema completo che migliori le loro capacità decisionali e ne agevoli le valutazioni. Inoltre, il progetto intende fornire alle persone meno esperte gli strumenti necessari per prendere decisioni informate in modo sicuro. Per conseguire questo obiettivo, il progetto impiega una serie di modelli matematici, algoritmi e dati medici che contribuiscono a migliorare l’efficienza delle decisioni.

Obiettivo

Physicians need to make many important decisions per day. One clinical example is the scheduling and dosage of chemotherapy treatments. A second example is the discrimination of atrial fibrillation from atypical atrial flutter, based on ECG data. Such important and complex decisions are usually based on expert knowledge, accumulated throughout the life of a physician and shaped by subjective (and sometimes unconscious) experience. It is not readily transferable and may be unavailable in rural areas. At the same time, the available imaging, laboratory, and basic clinical data is abundant and waits to be used. This data is not yet systematically integrated and often single data-points are used to make therapy decisions.

More and more clinical decision making tasks will be modeled in terms of mathematical relations.
I propose a systematic approach that supports and trains individual decision making. The developed ideas, mathematical models, and optimization algorithms will be generic and widely applicable in medicine and beyond, but also exploit specific structures, resulting in a patient- and circumstance-specific personalized medicine.

This allows, e.g. a physician to first simulate the impact of his decisions on a computer and to consider optimized solutions.
In the future, it will be the rare and unwanted exception that an important decision can not be backed up by consultation of a model-driven decision support system or based upon a systematic model-driven training.

MODEST has a mathematical core. It builds on a comprehensive, interdisciplinary work program, based on disciplinary expertise in mixed-integer optimal control and existing collaborations with medical and educational experts. It is both timely, given the increasing availability of data and the maturity of mathematical methods, models, and software; as well as high-impact, due to the large number of clinical areas that may benefit from optimization-based decision support and training tools.

Meccanismo di finanziamento

ERC-COG - Consolidator Grant

Istituzione ospitante

OTTO-VON-GUERICKE-UNIVERSITAET MAGDEBURG
Contribution nette de l'UE
€ 1 998 500,00
Indirizzo
UNIVERSITAETSPLATZ 2
39106 Magdeburg
Germania

Mostra sulla mappa

Regione
Sachsen-Anhalt Sachsen-Anhalt Magdeburg, Kreisfreie Stadt
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Costo totale
€ 1 998 500,00

Beneficiari (1)