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EurAsia Academy on Digital Pathology

Digital pathology (DP) and artificial intelligence (AI) have revolutionized the field of pathology. Although growing interest in DP & AI has been observed recently, there is still a reluctance to adopt this technology in routine clinical practice. Further, there is a need to harmonize this technology globally and bridge the knowledge gaps to get acquainted with the nuances of DP & AI. To this aim, we are pleased to announce the first-ever edition of the EurAsia Academy on Digital Pathology, an online event that will take place on October 10, 2023.

Organized by the European Society of Digital and Integrative Pathology (ESDIP), the Japanese Society of Digital Pathology (JSDP), and the Indian DP Interest Group, this event will bring together top-level experts from across the globe.

Throughout the day, pathologists, technicians, computer scientists, and clinicians, from entry-level to experienced users, will be able to follow online lectures that will cover major topics related to DP and AI. In this symposium, the following key areas will be addressed in two separate sessions:
1. Establishing and Transitioning to Digital Pathology
2. AI algorithms: From basics to clinical adoption

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MITEL in the Winners group at the AGGC22 Challenge, MICCAI 2022

MITEL ranked in the winners group at the AGGC22 Challenge, during MICCAI 2022. Team members: Kevin Roitero, Vincenzo Della Mea.

aggc22
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Best Practice Recommendations for the Implementation of a Digital Pathology Workflow

The European Society of Digital and Integrative Pathology (ESDIP) just published a paper on the implement Implementation of a Digital Pathology Workflow, with the participation of MITEL:

Fraggetta F, L’Imperio V, Ameisen D, Carvalho R, Leh S, Kiehl T-R, Serbanescu M, Racoceanu D, Della Mea V, Polonia A, Zerbe N, Eloy C. Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP). Diagnostics. 2021; 11(11):2167. https://doi.org/10.3390/diagnostics11112167

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UNIUD Daily Activities Accelerometer Dataset

We decided to make public a dataset we used for a work some year ago (accelerometer data for daily activities): UNIUD Daily Activities Accelerometer Dataset (UNIUD-DA-AD).

Available at:

-Github:  https://github.com/MITEL-UNIUD/UNIUD-DA-AD

-Kaggle:  https://www.kaggle.com/vdellamea/uniud-daily-activities-accelerometer-dataset/ 

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ESDIP Town Square Meeting: “Can I trust AI in Pathology?”

ESDIP Town Square Meeting
April 16, 2021 at 6 pm (CET)
“Can I trust AI in pathology?”

Dear All,

We are delighted to invite you to the ESDIP Town Square Meeting, a new series of informal events, starting on April 16, 2021, at 6:00 pm (CET) and aimed at promoting discussion around hot topics in digital and computational pathology.

Developed by the Educational Committee of ESDIP, under the supervision of Vincenzo Della Mea, from the University of Udine and Arvydas Laurinavičius from Vilnius University, this first meeting is titled “Can I trust AI in Pathology?”.




The main focus will be the role of artificial intelligence in pathology: the technology appears to be ready, but how reliable it is for the adoption in routine pathology practice?

The guests, Joe Saltz of the State University of New York at Stony Brook and Andrew Janowczyk of Case Western Reserve University, will briefly introduce their point of view about the title topic, then giving the floor to the public.

The valuable input from attendees, together with the expert views, will contribute to a better understanding of the advances as well as their possible clinical applications.

The workshop is free. You are welcome to attend, listen to the experts, and contribute with your viewpoint.To attend ESDIP Town Square Meeting, please send an email to 
admin@digitalpathologysociety.org until April 15, 2021. (Note: In case you have already submitted our registration and receive an email confirming it, please ignore this email). 

Sincerely,

Vincenzo Della Mea, Chair of the Educational Committee of ESDIP
On behalf of the Educational Committee of ESDIP

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Cause of death identification with deep learning

The last (open access) paper from our lab:

Underlying cause of death identification from death certificates using reverse coding to text and a NLP based deep learning approach

Vincenzo Della Mea, Mihai Horia Popescu, Kevin Roitero

Informatics in Medicine Unlocked, Volume 21, 2020, 100456

https://www.sciencedirect.com/science/article/pii/S2352914820306067

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Our paper on the HEROHE challenge

Our paper about the method that allowed us to reach the 2nd place in the HEROHE challenge is finally out:

La Barbera, D.; Polonia, A.; Roitero, K.; Econde-Sousa, E; Della Mea, V. Detection of HER2 from Haematoxylin-Eosin Slides Through a Cascade of Deep Learning Classifiers via Multi-Instance Learning. J. Imaging 2020, 6, 82.

https://www.mdpi.com/2313-433X/6/9/82

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I grafici di MITEL sul Messaggero Veneto

Da oggi i grafici reperibili all’indirizzo https://mitel.dimi.uniud.it/covid-19-fvg/ vengono pubblicati anche dal Messaggero Veneto.

mv
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Coronavirus in Friuli – Venezia Giulia

Una paginetta di riassunto veloce sulla situazione coronavirus in Friuli – Venezia Giulia, fatta sfruttando gli open data della Protezione Civile e la libreria charts.js:

https://mitel.dimi.uniud.it/covid-19-fvg/

covid-fvg
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LoRaWAN per applicazioni sociosanitarie

TOC-mini

Il Laboratorio MITEL, in collaborazione con Cimtech srl e MIPOT spa, ha appena pubblicato un articolo sulla rivista JMIR Medical Informatics (IF: 3.188) che riassume gli esiti del progetto PollicIoT riguardo l’applicabilità di LoRaWAN all’ambito sociosanitario: 

Della Mea V, Popescu MH, Gonano D, Petaros T, Emili I, Fattori MG. A Communication Infrastructure for the Health and Social Care Internet of Things: Proof-of-Concept Study. JMIR Med Inform 2020;8(2):e14583 DOI: 10.2196/14583

In sintesi: è un ottimo strumento per dispiegare rapidamente ed economicamente dispositivi IoT sanitari a casa dell’anziano o della persona fragile, purché i dispositivi non siano da usare in urgenza/emergenza o per scambiare grandi quantità di dati.

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