628 citations
- KTH Royal Institute of TechnologySE34 papers
- Karolinska University HospitalSE28 papers
- Stockholm UniversitySE18 papers
- Science for Life LaboratorySE14 papers
- Uppsala UniversitySE12 papers
- University of OxfordGB11 papers
- Centre National de la Recherche ScientifiqueFR10 papers
- King's College LondonGB8 papers
- Universidad de SevillaES8 papers
- University of CambridgeGB8 papers
- University of NamurBE8 papers
- King Abdullah University of Science and TechnologySA7 papers
206 papers
Distributed Lag Neural Additive Models
Calle Helmersson, Shivang Pandey, Leonardo Olivetti +1
We introduce Distributed Lag Neural Additive Models (DLNAMs), neural-additive analogues of Distributed Lag Non-linear Models (DLNMs) for learning nonlinear effects distributed over…
From Black Box to Glass Box: Cross-Model ASR Disagreement to Prioto Review in Ambient AI Scribe Documentation
Abdolamir Karbalaie, Fernando Seoane, Farhad Abtahi
Ambient AI "scribe" systems promise to reduce clinical documentation burden, but automatic speech recognition (ASR) errors can remain unnoticed without careful review, and high-qua…
AI-based Prediction of Biochemical Recurrence from Biopsy and Prostatectomy Samples
Andrea Camilloni, Chiara Micoli, Nita Mulliqi +11
Biochemical recurrence (BCR) after radical prostatectomy (RP) is a surrogate marker for aggressive prostate cancer with adverse outcomes, yet current prognostic tools remain imprec…
High Space-bandwidth Product Label-free Examination of iPSC-derived Brain Organoids via Fourier Ptychographic Microscopy
Mikolaj Krysa, Mikolaj Rogalski, Piotr Arcab +7
Fourier ptychographic microscopy (FPM) is a promising quantitative phase imaging technique that enables high-resolution, label-free imaging over a large field-of-view. Here, we pre…
Validation of Diagnostic Artificial Intelligence Models for Prostate Pathology in a Middle Eastern Cohort
Peshawa J. Muhammad Ali, Navin Vincent, Saman S. Abdulla +8
Background: Artificial intelligence (AI) is improving the efficiency and accuracy of cancer diagnostics. The performance of pathology AI systems has been almost exclusively evaluat…
Data Poisoning Vulnerabilities Across Healthcare AI Architectures: A Security Threat Analysis
Farhad Abtahi, Fernando Seoane, Iván Pau +1
Healthcare AI systems face major vulnerabilities to data poisoning that current defenses and regulations cannot adequately address. We analyzed eight attack scenarios in four categ…