Mar­co Gustav

Deep Learn­ing-based Bio­mark­ers for Pre­ci­sion Oncology

Abstract

The use of deep learn­ing (DL) in oncol­o­gy has opened a trans­for­ma­tive era for pre­ci­sion med­i­cine. This talk will focus on the devel­op­ment and val­i­da­tion of DL-based bio­mark­ers that have the poten­tial to advance can­cer diag­no­sis, prog­no­sis, and treat­ment. By uti­liz­ing the vast amounts of health­care data gen­er­at­ed by mod­ern tech­nolo­gies, DL algo­rithms can iden­ti­fy com­plex pat­terns – even those, which elude human detection.

These bio­mark­ers are impor­tant for under­stand­ing tumor biol­o­gy and patient het­ero­gene­ity, which can lead to more per­son­al­ized and effec­tive ther­a­peu­tic strate­gies. We exam­ine recent devel­op­ments in deep learn­ing tech­niques, the chal­lenges of inte­grat­ing arti­fi­cial intel­li­gence into clin­i­cal work­flows, and the impli­ca­tions of algo­rith­mic deci­sion mak­ing for patient care. 

Biography/​Link

Mar­co Gus­tav earned his Bachelor’s and Master’s degrees in Mechan­i­cal Engi­neer­ing from Leib­niz Uni­ver­si­ty Han­nover (LUH), Ger­many. He then worked as a Research Asso­ciate in Bio­ma­te­ri­als and Bio­me­chan­ics at Han­nover Med­ical School (MHH), where he focused on Ortho­pe­dic Implant Research and Deep Learn­ing for Gait Analysis.

Mar­co Gus­tav is cur­rent­ly pur­su­ing his PhD in Clin­i­cal Arti­fi­cial Intel­li­gence under the super­vi­sion of Prof. Jakob N. Kather at the Else Krön­er Fre­se­nius Cen­ter for Dig­i­tal Health, Dres­den Uni­ver­si­ty of Tech­nol­o­gy (TUD), Ger­many. His research focus­es on AI in med­i­cine, specif­i­cal­ly Com­pu­ta­tion­al Pathol­o­gy and Large Lan­guage Mod­els. He is pas­sion­ate about mak­ing AI in med­i­cine more acces­si­ble and under­stand­able for every­one, which he trans­lates into Sci­ence Slams.