Results 161 to 170 of about 86,909 (315)
On the performance of turbo codes and convolutional codes of low rate [PDF]
C.F. Leanderson+3 more
openalex +1 more source
ABSTRACT Aims To evaluate the diagnostic accuracy of periapical, bitewing or panoramic radiographs (standard 2D radiographs) in detecting and monitoring periodontitis (PICO 1) and to assess the clinical relevance of alternative and emerging diagnostic methods (e.g., cone‐beam computed tomography [CBCT], magnetic resonance imaging [MRI], ultrasound ...
Nicola Discepoli+4 more
wiley +1 more source
Performance of COFDM using turbo codes [PDF]
L. Sylla, Paul Fortier, H.T. Huynh
openalex +1 more source
Lower density of calretinin‐immunopositive neurons in the putamen of subjects with schizophrenia
Recent neuroimaging and histological studies highlight the striatum as a key area involved in SCH, but the specific impairment of neuronal subtypes in subcortical structures is not fully understood. This study is the first detailed investigation of neuroanatomical changes in the putamen in SCH, specifically examining the density of calretinin ...
Paz Kelmer+4 more
wiley +1 more source
rMATS-cloud: Large-scale Alternative Splicing Analysis in the Cloud. [PDF]
Adams JI+7 more
europepmc +1 more source
ABSTRACT Aim To examine the feasibility of using a large language model (LLM) as a screening tool during structured literature reviews to facilitate evidence‐based practice. Design A proof‐of‐concept study. Methods This paper outlines an innovative method of abstract screening using ChatGPT and computer coding for large scale, effective and efficient ...
Alexandra Mudd+5 more
wiley +1 more source
Harnessing advanced large language models in otolaryngology board examinations: an investigation using python and application programming interfaces. [PDF]
Hoch CC+9 more
europepmc +1 more source
Turbo Coding for Satellite and Wireless Communications
M. Reza Soleymani+2 more
openalex +1 more source
Coupled receiver-decoders for low rate turbo codes [PDF]
J. Hamikins, D. Divsalar
openalex +1 more source
Effective faking of verbal deception detection with target‐aligned adversarial attacks
Abstract Background Deception detection through analysing language is a promising avenue using both human judgements and automated machine learning judgements. For both forms of credibility assessment, automated adversarial attacks that rewrite deceptive statements to appear truthful pose a serious threat.
Bennett Kleinberg+2 more
wiley +1 more source