Results 71 to 80 of about 90,397 (281)

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

Approximate reasoning for real-time probabilistic processes

, 2004
We develop a pseudo-metric analogue of bisimulation for generalized semi-Markov processes. The kernel of this pseudo-metric corresponds to bisimulation; thus we have extended bisimulation for continuous-time probabilistic processes to a much broader ...
Alison L. Gibbs and Francis Edward Su, Josée Desharnais, Vineet Gupta, Radhakri, Marta Kwiatkowska, Prakash Panangaden, R. Segala and N. Lynch, Radha Jagadeesan, Vineet Gupta   +6 more
core   +7 more sources

Chameleon sequences reveal structural effects in proteins representing micelle‐like distribution of hydrophobicity

FEBS Open Bio, EarlyView.
Amino acids sequence of two different proteins with the same sequence (chameleon sequence—black boxes) represent in 3D structure of the proteins different secondary structures: HHHH—helical and BBB—Beta‐structural. The chains folded in water environment adopt different III‐order structures in which the chameleon fragments appear to adopt similar status
Irena Roterman, Katarzyna Stapor, Leszek Konieczny, Krzysztof Gądek, Piotr Nowakowski   +4 more
wiley   +1 more source

Digital twins to accelerate target identification and drug development for immune‐mediated disorders

FEBS Open Bio, EarlyView.
Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley   +1 more source

Abstract Hidden Markov Models: a monadic account of quantitative information flow

, 2019
Hidden Markov Models, HMM's, are mathematical models of Markov processes with state that is hidden, but from which information can leak. They are typically represented as 3-way joint-probability distributions.
McIver, Annabelle, Morgan, Carroll, Rabehaja, Tahiry   +2 more
core   +1 more source

Visual Recovery Reflects Cortical MeCP2 Sensitivity in Rett Syndrome

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Rett syndrome (RTT) is a devastating neurodevelopmental disorder with developmental regression affecting motor, sensory, and cognitive functions. Sensory disruptions contribute to the complex behavioral and cognitive difficulties and represent an important target for therapeutic interventions.
Alex Joseph Simon, Nathalie Picard, Valeria d'Andrea, Enchi Chang, Joseph Leffler, Eleonora Centofante, Matthew Taylor, Francesca Bardi, Francesca Cavicchiolo, Takao K. Hensch, Stefano Panzeri, Chinfei Chen, Michela Fagiolini   +12 more
wiley   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

On compactness of probabilistic metric space

Applied Mathematical Sciences, 2014
In this paper we show that every separable probabilistic metric space admits a compatible precompact probabilistic metric and that a probabilistic metric space is compact if and only if is precompact and complete. Finally we give a generalization Niemytzki-Tychonoff theorem [1] to probabilistic metric spaces.
Abderrahim Mbarki, Abedelmalek Ouahab, Naciri Rachid   +2 more
openaire   +1 more source