PROSTATE CANCER PROJECT

Prostate cancer care

Prevent, detect, diagnose, treat, care

- Faster decisions, predict tumor activity, grading, reduce biopsies. AI based Gleason grading
- Analyze all types of variables, from lifestyle habits to biomarkers, predict genomic abnormalities..
- Find similarity between patients, to create related networks, classify documents and patients, create groups, identify suitable patients for clinical trials..
- Integration of data from multiple domains in the decision-making process
- Image processing, automatic segmentation, lesion detection, staging..
- Generation of diagnostic, prognostic, risk and predictive biomarkers
- Causal inference, econometrics and statistics, machine learning, deep learning, nlp, graph theory, games theory..

The power of text

Discover the unimagined

- Establish NEW variables through NLP, annotations, clinical reports..
- Find named entities: hospitals, research institutes, leading researchers, studies, diseases, locations, symptoms, medications, biomarkers. Entity linking.
- Patient stratification, identify, categorize and encode medical and patient data, identify patterns and trends of disease progression, responses to treatments such as adverse reactions, success, preventing relevant data from being overlooked
- Sentiment analysis, trends, intentions, suicide.. in documents. Information chatbots.
- Smart, contextual and related search engine: reports, patients, symptoms, relationships, images, important clinical findings.
- Generate information summaries, descriptive reports and recommendations from images, analytical tests, x-rays, MRI, CT scans, ultrasounds, patient histories, negligible or not known problem or symptom..

World information

Recovering public information

- OSINT (Open Source INTelligence)

- Prostate cANcer graDe Assessment (PANDA) Challenge

- Medical Outcomes Partnership (OMOP) Common Data Model (CDM)

- Scientific publications. Explore and recover information for scientific publications around the world

- Public datasets. Universities, hospitals, researches, public administrations statistics..

- Creative commons published books

- Congress

- Public IA algorithms

Artificial Intelligence: skin cancer care in people with albinism

In sub-Saharan Africa live 200.000 people with albinism with no education or access to the protection from the sun that they need. In addition to being discriminated against for their appearance and persecuted by the influence of violent superstitions, the main cause of their extreme vulnerability is the sun: skin cancer ends the life of 9 out of 10 people with albinism before reaching the age of 30.

In Africa, skin cancer is the leading cause of death among people with albinism, ending their lives dramatically at an early age. Prevention is essential. In Africa, sunscreen saves lives.

AI based software for hospitals for:

Beyond Suncare

Chatbot for prostate cancer care for FEFOC

Using Large Language Models

For:

FEFOC
Try FEFOC Chatbot

Chatbot for cancer care for Fundación MÁS QUE IDEAS

Using Large Language Models

(Project in progress) for:

Fundación MÁS QUE IDEAS

Surveys

Several surveys for institutions or conferences:

Click here