New directions for deep learning in cancer research through concept explainabili...
New directions for deep learning in cancer research through concept explainability and virtual experimentation.
Deep learning (DL) is rapidly transforming cancer research and oncology. DL can extract subtle visual features from preclinical and clinical image data. In my junior research group, I have developed end-to-end DL methods to predic...
Deep learning (DL) is rapidly transforming cancer research and oncology. DL can extract subtle visual features from preclinical and clinical image data. In my junior research group, I have developed end-to-end DL methods to predict molecular biomarkers and clinical outcomes directly from histopathology slides. Because histopathology slides are ubiquitously available for any patient with a solid tumor, DL is a broad tool for translational studies, enabling researchers to extract molecular information and make predictions about clinical outcome.
However, the potential of DL in cancer research is fundamentally limited because it is purely descriptive and, in many cases, a black-box system. Also, DL is currently disjoint from the vast amount of biological mechanistic knowledge in cancer research, and from the world of experimentation. In NADIR, I will close this gap. My hypothesis is that DL models can not only make predictions but can be used to verify
existing biological knowledge and to make new mechanistic discoveries. The main tools that allow me to address this are concept explainability and counterfactual virtual experimentation. For both, there exists a nonmedical proof of concept, but no systematic biomedical application yet. I approach this problem as a biomedical cancer researcher with training in programming, medical image analysis, and biomedical engineering. As such, I will develop DL systems that can extract biological concepts, can elucidate biological mechanisms, and can be used to create, and answer, mechanistic hypotheses. NADIR’s tools will be synergistic with and can be used together with other biological high-throughput experimentation pipelines such as transgenic animal experiments or tumor organoid cultures. The main use case of NADIR is focused on tumor-immune interaction in colorectal and gastric cancer, and through the educational and outreach program in NADIR, it will be made available as a general tool for cancer researchers in biomedicine.ver más
02-11-2024:
Generación Fotovolt...
Se ha cerrado la línea de ayuda pública: Subvenciones destinadas al fomento de la generación fotovoltaica en espacios antropizados en Canarias, 2024
01-11-2024:
ENESA
En las últimas 48 horas el Organismo ENESA ha otorgado 6 concesiones
01-11-2024:
FEGA
En las últimas 48 horas el Organismo FEGA ha otorgado 1667 concesiones
Seleccionando "Aceptar todas las cookies" acepta el uso de cookies para ayudarnos a brindarle una mejor experiencia de usuario y para analizar el uso del sitio web. Al hacer clic en "Ajustar tus preferencias" puede elegir qué cookies permitir. Solo las cookies esenciales son necesarias para el correcto funcionamiento de nuestro sitio web y no se pueden rechazar.
Cookie settings
Nuestro sitio web almacena cuatro tipos de cookies. En cualquier momento puede elegir qué cookies acepta y cuáles rechaza. Puede obtener más información sobre qué son las cookies y qué tipos de cookies almacenamos en nuestra Política de cookies.
Son necesarias por razones técnicas. Sin ellas, este sitio web podría no funcionar correctamente.
Son necesarias para una funcionalidad específica en el sitio web. Sin ellos, algunas características pueden estar deshabilitadas.
Nos permite analizar el uso del sitio web y mejorar la experiencia del visitante.
Nos permite personalizar su experiencia y enviarle contenido y ofertas relevantes, en este sitio web y en otros sitios web.