21 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Humanitas UniversityIT5 papers
- Politecnico di MilanoIT4 papers
- Human TechnopoleIT3 papers
- Aarhus UniversityDK1 paper
- Centre de Biologie pour la Gestion des PopulationsFR1 paper
- Centre Hospitalier Universitaire de GrenobleFR1 paper
- Charité - Universitätsmedizin BerlinDE1 paper
- École Polytechnique Fédérale de LausanneCH1 paper
- Energy InstituteGB1 paper
- Evelina London Children's HealthcareGB1 paper
- Grenoble Institute of NeurosciencesFR1 paper
- Harvard UniversityUS1 paper
7 papers
Artificial intelligence in deep brain stimulation for movement disorders: a systematic review and technology readiness assessment
Zohra Souei, Muhammad Mushhood Ur Rehman, Harith Akram +14
Artificial intelligence (AI) is increasingly explored across deep brain stimulation (DBS) for movement disorders, yet whether current systems are approaching deployment remains unc…
A Closer Look at AUROC and AUPRC under Class Imbalance
Matthew B. A. McDermott, Haoran Zhang, Lasse Hyldig Hansen +2
In machine learning (ML), a widespread claim is that the area under the precision-recall curve (AUPRC) is a superior metric for model comparison to the area under the receiver oper…
A comprehensive comparison of tools for fitting mutational signatures
Matúš Medo, Charlotte K. Y. Ng, Michaela Medová
Mutational signatures connect characteristic mutational patterns in the genome with biological or chemical processes that take place in cancers. Analysis of mutational signatures c…
Segmentation of Planning Target Volume in CT Series for Total Marrow Irradiation Using U-Net
Ricardo Coimbra Brioso, Damiano Dei, Ciro Franzese +4
Radiotherapy (RT) is a key component in the treatment of various cancers, including Acute Lymphocytic Leukemia (ALL) and Acute Myelogenous Leukemia (AML). Precise delineation of or…
Ensemble Methods for Multi-Organ Segmentation in CT Series
Leonardo Crespi, Paolo Roncaglioni, Damiano Dei +5
In the medical images field, semantic segmentation is one of the most important, yet difficult and time-consuming tasks to be performed by physicians. Thanks to the recent advancem…
Imaging-based representation and stratification of intra-tumor Heterogeneity via tree-edit distance
Lara Cavinato, Matteo Pegoraro, Alessandra Ragni +3
Personalized medicine is the future of medical practice. In oncology, tumor heterogeneity assessment represents a pivotal step for effective treatment planning and prognosis predic…
Chest X-Rays Image Classification from beta-Variational Autoencoders Latent Features
Leonardo Crespi, Daniele Loiacono, Arturo Chiti
Chest X-Ray (CXR) is one of the most common diagnostic techniques used in everyday clinical practice all around the world. We hereby present a work which intends to investigate and…