{"id":7373,"date":"2023-04-21T13:02:43","date_gmt":"2023-04-21T11:02:43","guid":{"rendered":"https:\/\/www.convegnonazionaleaiic.it\/artificial-intelligence-based-web-platform-for-digital-neurology\/"},"modified":"2023-04-21T13:02:43","modified_gmt":"2023-04-21T11:02:43","slug":"artificial-intelligence-based-web-platform-for-digital-neurology","status":"publish","type":"post","link":"https:\/\/www.convegnonazionaleaiic.it\/artificial-intelligence-based-web-platform-for-digital-neurology\/","title":{"rendered":"ARTIFICIAL INTELLIGENCE BASED WEB PLATFORM FOR DIGITAL NEUROLOGY"},"content":{"rendered":"
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AFFILIAZIONE<\/span>
\n<\/strong>technoscience – universit\u00e0 san raffaele roma<\/p>\n

AUTORE PRINCIPALE<\/span>
\n<\/strong>Prof. Pallotti Antonio<\/p>\n

\nVALUTA IL CHALLENGE<\/span><\/strong>[ratingwidget]<\/p>\n<\/div>\n

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GRUPPO DI LAVORO<\/span><\/strong>
\nDott.ssa Calabrese Raffaella<\/strong> – universit\u00e0 san raffaele roma, roma<\/i>
Dott.ssa Mancini Annalisa<\/strong> – universit\u00e0 degli studi di roma “la sapienza”, roma<\/i>
Dott. Angelucci Matteo<\/strong> – universit\u00e0 san raffaele roma, roma<\/i>
Prof. Pallotti Antonio<\/strong> – technoscience – universit\u00e0 san raffaele roma, roma<\/i> <\/p>\n

AREA TEMATICA<\/span>
\n<\/strong>Applicazioni di intelligenza artificiale in sanit\u00e0<\/p>\n

ABSTRACT<\/span>
\n<\/strong>Worldwide, Parkinson\u2019s disease (PD) is one of the most common neurodegenerative diseases affecting millions of people.
\nOver the past 25 years, there has been a considerable evolution regarding Parkinson\u2019s diagnosis; initially, the only available tools were neurological examinations and autopsies. Subsequently, brain scintigraphy with DATSCAN\uf0d2 was introduced and, in recent years, it has been added the magnetic resonance, an examination that doesn\u2019t use ionizing radiation, but only involves exposure to a magnetic field, capable of identifying neuromelanin\u2019s changes, visible as contrast reduction.<\/p>\n

In literature several studies have shown how impaired writing and vocal insufficiencies are important elements for the early detection of disease.
\nIn 2021, two studies by our research group on Parkinson\u2019s classification through Telemedicine tools were carried out, one on grafh signal (77.5% accuracy), and the other on Voice signal (91.2%). <\/p>\n

The objective of our preliminary study is the development of a telemonitoring system of the voice and graph signal for neurological diseases\u2019 screening such as Parkinson\u2019s, thanks to artificial intelligence techniques (machine learning).<\/p>\n

The system is based on a simple Android\/iOS application (on a smartphone or tablet), in which two tasks are required. The first one is vocal, and it consists of sounds recording, while the second one is related of writing letters and drawing geometric shapes. We enrolled 2 subjects, one healthy and the other one with advanced PD.
\nData are acquired via Bluetooth wireless communication, stored locally, and sent to a web platform. Those data can be used to be processed both with standard analyses and through machine learning models (Artificial Intelligence) to support the specialist decision.
\nImmediately afterwards, the two subjects underwent an MRI of the brain. The images are sent to the web platform and saved together with the data acquired through the application.<\/p>\n

Compared to previous research that used a professional tablet, a digital pen, and a microphone, our study introduced two novelties: the use of smartphones and tablets, and the archiving of radiological images on a platform.
\nIn conclusion, this system is a disease development control\/monitoring tool that could save patients\u2019 time, allowing specialists to have all the patient’s clinical and instrumental data on the platform, and having a positive impact on hospitals\u2019 resources.<\/p>\n

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