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Genomics and Personalized Medicine for all though Artificial Intelligence in Haematological Diseases

Risultati finali

Data processing, data management plan and GDPR compliance report

This deliverable will specify the intended data sources data flows and data processing across the consortium and its work plan to form a complete Data Management Plan It will confirm the completion of a DPIA at each relevant partner site and summarise the main areas of risk and mitigation identified It will confirm the legal basis for the processing of each data source noting these will all be special category data and will include copies of approved consent forms in cases where consent is the legal basis

Data homogenisation requirements and specifications

This report will define the data homogenisation processes to be included in GENOMED4ALL

Literature mining and preprocessing.

Literature mining and first AI software release data preprocessing and statistical data cleaning All the software will be open source R Python and C and will be made available for the other project partners

Report 1 of the EAB

This will be the first report of the EAB Including its terms of reference and constitution plus its initial appraisal of the intended data protection human ethics and artificial intelligence approaches

GENOMED4ALL standardization plan

This deliverable will recommend adapt and calibrate data standards for data collected from different clinical partners

GENOMED4ALL Impact Master Plan

A document outlining the project dissemination communication exploitation strategies and detailing the project plan of concrete GENOMED4ALL activities including project website

Preliminary conclusions about federated learning applied to clinical data.

Federated learning software release and report

Hybrid Federated learning model.

This deliverable will describe the AI learning mechanisms to make sure a hybrid approach using federated and centralised learning scheme can be applied to GENOMED4ALL

Pubblicazioni

GENOMED4ALL: Improving MDS Classification and Prognosis by AI (Clinical Study)

Autori: F. Álvarez, L. Comnes, M.D.M Mañú et al
Pubblicato in: 2021
Editore: N/A

GenoMed4All: Artificial Intelligence-based Deep Learning algorithms for patients with Sickle Cell Disease

Autori: A. Idrizovic, S. van der Veen, M.D.M Mañu, A. Collado, R. Colombatti, M.P. Boaro, P. Bartolucci, M. de Montalembert, M.H. Cnossen, B.J. Biemond, M. Kleanthous, E.J. van Beers, P. Kountouris
Pubblicato in: 2022
Editore: N/A
DOI: 10.5281/zenodo.6583445

A Sex-Informed Approach to Improve Prognostication and Personalized Decision-Making Process in Myelodysplastic Syndromes. a European Study of 11.878 Patients

Autori: G. Maggioni, E. Travaglino, A. Alfonso Pierola et al
Pubblicato in: Blood journal, Issue Weekly, 2020, ISSN 0006-4971
Editore: American Society of Hematology
DOI: 10.1182/blood-2020-138775

Protein Stability Perturbation Contributes to the Loss of Function in Haploinsufficient Genes

Autori: G. Birolo, S. Benevenuta, P. Fariselli, E. Capriotti, E. Giorgio and T. Sanavia
Pubblicato in: Frontiers in Molecular Biosciences, 2020, ISSN 2296-889X
Editore: Frontiers Media S.A.,
DOI: 10.3389/fmolb.2021.620793

Clinical relevance of clonal hematopoiesis in persons aged ≥80 years

Autori: M. Rossi, M. Meggendorfer, M. Zampini et al
Pubblicato in: Blood journal, Issue Weekly, 2021, ISSN 0006-4971
Editore: American Society of Hematology
DOI: 10.1182/blood.2021011320

Integrative diagnosis of sickle cell disease patients for personalized medicine

Autori: A. Idrizovic, A. Collado, E.J. van Beers, R. Colombatti, P. Bartolucci, M. de Montalembert, M.P. Boaro, D. Beneitez, A. Ortuño, A. Ruiz, I. Isola, E. Cela, R. van Wijk, M. Rab, M.D.M. Mañú
Pubblicato in: 4th. Global Congress on Sickle Cell Disease, 2022
Editore: Global Sickle Cell Disease Network

O-02: RADIOMICS AND ARTIFICIAL INTELLIGENCE FOR IDENTIFICATION AND MONITORING OF SILENT CEREBRAL INFARCTS IN SICKLE CELL DISEASE: FIRST ANALYSIS FROM THE GENOMED4ALL EUROPEAN PROJECT

Autori: R., BIONDI; M., BOARO; N., BIONDINI; A., COLLADO GIMBERT; J., ESCUDERO FERNANDEZ; V., PINTO5; N., ROMANO; V., VOI7; G., FERRERO; M., CASALE; M., CIRILLO; G., PALAZZI; F., CAVALLERI; G., FORNI5; G., REGGIANI; S., PERROTTA; M., MANU PEREIRA; S., ZAZO; K., MARIAS; M., DE MONTALEMBERT; P., BARTOLUCCI; E., VANBEERS; F., ALVAREZ; F., CREMONESI; T., SANAVIA; P., FARISELLI; G., CASTELLANI; R., MANARA; R.,
Pubblicato in: 2022
Editore: Wolters Kluwer Health, Inc.
DOI: 10.1097/01.hs9.0000872816.60309.4c

Radiomics and artificial intelligence for identification and monitoring of silent cerebral infarcts in sickle cell disease: first analysis from the GENOMED4ALL European project

Autori: R. Biondi, M.P. Boaro, N. Biondini et al
Pubblicato in: EHA2022 Congress, 2022
Editore: European Hematology Association (Wolters Kluwer Health, Inc)

2,3-DIPHOSPHOGLYCERATE DETECTION VIA DIRECT INFUSION HIGH RESOLUTION MASS SPECTROMETRY CORRELATES WITH QUANTITATIVE DETECTION IN BLOOD OF PATIENTS WITH SICKLE CELL DISEASE

Autori: S. van der Veen, M.J. van Dijk, J.J.M. Jans, N.M. Verhoeven-Duif, R. van Wijk, M. Bartels, M.D.M. Mañú Pereira, R. Colombatti, M. Martella, V. Munaretto, M.P. Boaro, P. Bartolucci, M.H. Cnossen, B.J. Biemond, E.J. van Beers
Pubblicato in: EHA2022 Congress, 2022
Editore: European Hematology Association

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