Results 91 to 100 of about 32,991,499 (363)
Benchmarking alternative interpretable machine learning models for corporate probability of default
In this study we investigate alternative interpretable machine learning ("IML") models in the context of probability of default ("PD") modeling for the large corporate asset class.
Michael Jacobs, Jr
doaj +1 more source
The communication strategy for the release of the first European Seismic Risk Model and the updated European Seismic Hazard Model [PDF]
To design user-centred and scientifically high-quality outreach products to inform about earthquake-related hazards and the associated risk, a close collaboration between the model developers and communication experts is needed.
I. Dallo+21 more
doaj +1 more source
Prediction models in health care aim to predict for an individual whether a particular outcome, such as disease, is present (diagnostic models) or whether it will occur in the future (prognostic models) (16).
K. Moons+8 more
semanticscholar +1 more source
B cells sense external mechanical forces and convert them into biochemical signals through mechanotransduction. Understanding how malignant B cells respond to physical stimuli represents a groundbreaking area of research. This review examines the key mechano‐related molecules and pathways in B lymphocytes, highlights the most relevant techniques to ...
Marta Sampietro+2 more
wiley +1 more source
A Contextual Risk Model for the Ellsberg Paradox
The Allais and Ellsberg paradoxes show that the expected utility hypothesis and Savage's Sure-Thing Principle are violated in real life decisions. The popular explanation in terms of 'ambiguity aversion' is not completely accepted.
Aerts, Diederik, Sozzo, Sandro
core +1 more source
Evolutionary interplay between viruses and R‐loops
Viruses interact with specialized nucleic acid structures called R‐loops to influence host transcription, epigenetic states, latency, and immune evasion. This Perspective examines the roles of R‐loops in viral replication, integration, and silencing, and how viruses co‐opt or avoid these structures.
Zsolt Karányi+4 more
wiley +1 more source
Model uncertainty: When modeling risk leads to a pretense of knowledge
The main purpose of the paper is to develop a concept of model uncertainty as opposed to the existing and well-established concept of model risk. Up to date the broad literature on probability not only developed complete probability systems, but also ...
Mateusz Machaj
doaj +1 more source
Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever+1 more
wiley +1 more source
Cancer‐associated fibroblasts (CAFs) promote cancer growth, invasion (metastasis), and drug resistance. Here, we identified functional and diverse circulating CAFs (cCAFs) in patients with metastatic prostate cancer (mPCa). cCAFs were found in higher numbers and were functional and diverse in mPCa patients versus healthy individuals, suggesting their ...
Richell Booijink+6 more
wiley +1 more source
Surfaceome: a new era in the discovery of immune evasion mechanisms of circulating tumor cells
In the era of immunotherapies, many patients either do not respond or eventually develop resistance. We propose to pave the way for proteomic analysis of surface‐expressed proteins called surfaceome, of circulating tumor cells. This approach seeks to identify immune evasion mechanisms and discover potential therapeutic targets. Circulating tumor cells (
Doryan Masmoudi+3 more
wiley +1 more source