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Inteligencia artificial (IA) al servicio de la investigación de correlaciones y tratamiento mejorado de múltiples enfermedades crónicas

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TOGR20180918001
Publicado:
26/09/2018
Caducidad:
27/09/2019
Resumen:
Una empresa griega del sector de TI especializada en inteligencia artificial (IA) ofrece un método novedoso para buscar correlaciones entre enfermedades crónicas analizando los datos de la medicación del paciente. Este método crea el conocimiento adecuado y necesario y predice enfermedades múltiples, su evolución, su relación con los aspectos socioeconómicos y epidemias, su impacto económico en la asistencia sanitaria, etc. El paso siguiente es conectar el sistema con aplicaciones empleadas por los pacientes a nivel personal o con el sistema sanitario (hospitales, médicos, etc.). La empresa busca hospitales, participantes en el sistema sanitario, compañías informáticas y otros socios con el fin de establecer acuerdos de cooperación en materia de investigación y ampliar el método a otros conjuntos de datos.

Details

Tittle:
Artificial Intelligence (AI) in the service of investigating the correlations and the enhanced treating of the multiple chronic diseases
Summary:
A Greek IT company dealing with Artificial Intelligence (AI). The company is presenting an innovative method to search for corellations between chronic diseases by analysing the data of the medication of the patients. The company is open for technical or research collaborations with hospitals, healthcare system stakeholders, IT companies and other partners for further expanding the method to other data-sets.
Description:
A modern challenge is the management of what many health experts refer to as multiple chronic conditions by multiple chronic diseases. In fact, estimates suggest that about two-thirds of older adults live with two or more chronic conditions. The constantly ageing population will only increase the magnitude of this challenge. Chronic conditions require ongoing medical attention and/or limit activities of daily living. Examples include arthritis, diabetes, heart disease and hypertension, as well as some psychological disorders like depression.

Although most individuals have more than one chronic condition, the health care system is primarily organized to provide care on a disease-by-disease basis. Therefore, when individuals consult several specialists, the opportunity for confusion escalates. The most common example involves the use of multiple medications. The use of one may contraindicate the use of another. This situation can result in fragmented, expensive and sometimes inefficient care. Care coordination is the missing link here. If care is coordinated then medical and social service providers bring their respective expertise to bear on each individual´s health problems in the most effective and coordinated manner.

A Greek SME company dealing with the development of Artificial Intelligence (AI) solutions presents a novel approach towards the effective management of the complex medication. The Greek company developed a method for creating the right and necessary knowledge and prediction concerning multiple diseases, their evolution, their relation with socio-economic conditions as well as epidemics, their economic impact on health care, etc. The company designed the AI approach with a machine learning methodology, accompanied by suitable tools and performed tests with real data. The company used a series of anonymous proofs of purchase from a sample of pharmacies from Greece and France. The route that the company followed was first the active substance then the commercial name of the medicine and in the end the proof of purchase. The company started by creating a clustering tool learning from monthly data, a tool that discovers clusters of multiple diseases patients. The company discovered 25 distinct clusters. Those clusters were checked by doctors who verified their significance and their existence in real life. This resulted to the knowledge of the medicines (and therefore the active substances) that consumed from the same group of people. By applying the developed methodology in these data sets, the company identified correlations between active substances of medicines administered to patients and onset or deterioration of another disease, as a result of the treatment with this substance.

The initial results showed that there is a significant field for research -Y- development using AI. As an example, the company identified a major cluster of patients with cardiovascular disease and cholesterol. This cluster of patients is taking 4 major substances, one used for treating cardiovascular diseases, two more for cholesterol and surprisingly most of the patients are taking an antidepressant one. Regarding other medications, in this specific cluster, the company observed that the patients are also taking medication for stomach problems due to cardiovascular treatment. There is also a trend in this cluster to use antidepressant, something that was not known and measured till now.

The Greek company is looking for multiple partners dealing with the medical care or management of patients with multiple chronic diseases for technological or potential research collaboration.
Advantages and Innovations:
The objective of the company is to leverage AI in order to offer better conditions to patients and reduce significantly healthcare cost. The approach is innovative. By using the existing data, in the proof of purchases and the clustering of patients, the Greek company can reveal correlations of multiple diseases.
This approach offers proper knowledge necessary for revealing correlations between the different medications taken by the patients for treating multimorbidity. This advanced knowledge can be the basis for a health care system in order to understand and prevent diseases, as well as serving the patients better and reducing the cost of healthcare. Next step for the Greek company is to connect this system with applications used by patients in a personal level or the health care system (hospitals, doctors, etc).
The proposed approach also classifies patients and their behaviours as the most optimum for a given action to take and at the same time predicts future attitudes and results of this action.
Stage of Development:
Available for demonstration
IPs:
Secret Know-how

Partner sought

Type and Role of Partner Sought:
The Greek company is looking for multiple collaborators. Hospitals, public healthcare institutions, IT companies dealing with medical data, pharmaceutical companies, associations of doctors or other similar entities dealing with patients with multiple chronic diseases. The company would like to collaborate on the expansion of the system, including more diseases, receiving scientific consultation from doctors, searching new fields of data mining, new correlations and clustering groups. The basis of the collaboration will be the use of AI and the available data.

The collaborations sought could be technical or research for the further expansion of the system. The Greek company is willing to collaborate with partners in order to search more corellations from data provided by the partner. Also a research collaboration in the form of a research project (H2020 for example) is sought.

Client

Type and Size of Client:
Industry SME 11-49
Already Engaged in Trans-National Cooperation:
Si
Languages Spoken:
English
French
Greek

Keywords

Technology Keywords:
01004001 Applications for Health
01003003 Artificial Intelligence (AI)
01003010 Databases, Database Management, Data Mining