Results 161 to 170 of about 644,385 (252)

Comparing supervised machine learning and large language models in title-abstract screening. [PDF]

Syst Rev
Aigner MF, Ganzinger M, Probst P, Rinckens M, Pausch TM.   +4 more
europepmc   +1 more source

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source

Fuzzy Clustering Models for Gene Expression Data Analysis

With the advent of microarray technology, it is possible to monitor gene expression of tens of thousands of genes in parallel. In order to gain useful biological knowledge, it is necessary to study the data and identify the underlying patterns, which ...
Wang, Yu
core  

Unimodal vs. multimodal deep learning for non-invasive MGMT promoter methylation prediction in glioblastoma: A systematic evaluation on the BraTS 2021 dataset. [PDF]

PLoS One
Oulia F, Charton P, Kabir M, Gardebien F, Damour C, Cadet F.   +5 more
europepmc   +1 more source

Intelligent Tutoring Systems for Adult Learning in STEM Disciplines

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Intelligent tutoring systems (ITS) are reshaping adult learning in STEM by providing adaptive, data‐driven instruction across classrooms, workplaces, and informal environments. In the context of ITS, this article compares generative AI, which creates personalized explanations and practice materials, with explainable AI, which focuses on ...
Jill Zarestky, Amanda R. Lager Gleason
wiley   +1 more source

Data Structures and Algorithms - Abstract Data Types Part 2

An Abstract Data Type (ADT) defines: A well-specified collection of data (data state) A set of operations that can be performed upon the data Abstract – does not say anything about the details of how it actually works. To use data in a program, in
Devon, Jim, Paterson, James
core  

Classified algebras [PDF]

We present a new formal system for the specification and verification of abstract data types, one which allows subtypes and polymorphism. The new system is based on a modified notion of algebra, namely that of classified algebra.
Wadge, William W.
core  

A large Chinese dataset of ten-category semantic relations with developmental performance in children and adolescents. [PDF]

Sci Data
Fu J, Liu C, Mou S, Shi L, Zhang L, Peng X, Li T, Hu H, Fu M, Xue G.   +9 more
europepmc   +1 more source

Super‐Refractory Status Epilepticus (SRSE) in a Patient With Compound Heterozygous OPA1 Variants: Case Report and Literature Review

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi, Lara Basovic, Christopher Michael McGraw   +2 more
wiley   +1 more source

Extensible automated constraint modelling via refinement of abstract problem specifications

, 2015
Constraint Programming (CP) is a powerful technique for solving large-scale combinatorial (optimisation) problems. Constraint solving a given problem proceeds in two phases: modelling and solving. Effective modelling has an huge impact on the performance
Akgün, Özgür
core