Results 51 to 60 of about 1,028,836 (338)

Adverse prognosis gene expression patterns in metastatic castration‐resistant prostate cancer

Molecular Oncology, EarlyView.
We aggregated a cohort of 1012 mCRPC tissue samples from 769 patients and investigated the association of gene expression‐based pathways with clinical outcomes. Loss of AR signaling, high proliferation, and a glycolytic phenotype were independently prognostic for poor outcomes, and an adverse transcriptional feature score incorporating these pathways ...
Marina N. Sharifi, Eric Feng, Nicholas R. Rydzewski, Amy K. Taylor, Jamie M. Sperger, Yue Shi, Kyle T. Helzer, Matthew L. Bootsma, Viridiana Carreno, Alex H. Chang, Luke A. Nunamaker, Grace C. Blitzer, Tianfu Andy Shang, Aishwarya Subramanian, Anders Bjartell, Andreas Josefsson, Pernilla Wikström, Emily Feng, Manish Kohli, Rendong Yang, Scott M. Dehm, Eric J. Small, Rahul Aggarwal, David A. Quigley, Joshua M. Lang, Shuang G. Zhao, Martin Sjöström   +26 more
wiley   +1 more source

Investigation of DNN-HMM and Lattice Free Maximum Mutual Information Approaches for Impaired Speech Recognition

IEEE Access, 2021
Assistive tools that recognize impaired speech due to neurological disorders are emerging and its a fairly complex task. An Intelligent Impaired Speech Recognition system helps persons with speech impairment to improve their interactions with outside ...
Vishnika Veni S, Chandrakala S
doaj   +1 more source

Two and three-dimensional visual articulatory models for pronunciation training and for treatment of speech disorders [PDF]

, 2008
Visual articulatory models can be used for visualizing vocal tract articulatory speech movements. This information may be helpful in pronunciation training or in therapy of speech disorders.
Graf-Borttscheller, Verena, Kröger, Bernd J., Lowit, Anja   +2 more
core  

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

Molecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

A Protection Scheme With Speech Processing Against Audio Adversarial Examples

IEEE Access
Machine learning technologies have improved the accuracy of speech recognition systems, and devices using those systems, such as smart speakers and AI assistants, are now in wide use. However, speech recognition systems have security vulnerabilities.
Yuya Tarutani, Taisei Yamamoto, Yukinobu Fukushima, Tokumi Yokohira   +3 more
doaj   +1 more source

Why has (reasonably accurate) Automatic Speech Recognition been so hard to achieve? [PDF]

, 2009
Hidden Markov models (HMMs) have been successfully applied to automatic speech recognition for more than 35 years in spite of the fact that a key HMM assumption -- the statistical independence of frames -- is obviously violated by speech data.
Gillick, Larry, Wegmann, Steven
core  

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

Chemoresistome mapping in individual breast cancer patients unravels diversity in dynamic transcriptional adaptation

Molecular Oncology, EarlyView.
This study used longitudinal transcriptomics and gene‐pattern classification to uncover patient‐specific mechanisms of chemotherapy resistance in breast cancer. Findings reveal preexisting drug‐tolerant states in primary tumors and diverse gene rewiring patterns across patients, converging on a few dysregulated functional modules. Despite receiving the
Maya Dadiani, Gilgi Friedlander, Gili Perry, Nora Balint‐Lahat, Shlomit Gilad, Dana Morzaev‐Sulzbach, Anjana Shenoy, Noa Bossel Ben‐Moshe, Anya Pavlovsky, Rinat Bernstein‐Molho, Eytan Domany, Iris Barshack, Tamar Geiger, Bella Kaufman, Einav Nili Gal‐Yam   +14 more
wiley   +1 more source

Speech Recognition for the iCub Platform [PDF]

Frontiers in Robotics and AI, 2018
This paper describes open source software (available at https://github.com/robotology/natural-speech) to build automatic speech recognition (ASR) systems and run them within the YARP platform. The toolkit is designed (i) to allow non-ASR experts to easily create their own ASR system and run it on iCub and (ii) to build deep learning-based models ...
Bertrand Higy, Bertrand Higy, Alessio Mereta, Giorgio Metta, Leonardo Badino   +4 more
openaire   +5 more sources

Landscape of BRAF transcript variants in human cancer

Molecular Oncology, EarlyView.
We investigate the annotation of BRAF variants, focusing on protein‐coding BRAF‐220 (formerly BRAF‐reference) and BRAF‐204 (BRAF‐X1). The IsoWorm pipeline allows us to quantify these variants in human cancer, starting from RNA‐sequencing data. BRAF‐204 is more abundant than BRAF‐220 and impacts patient survival.
Maurizio S. Podda, Danilo Tatoni, Gianluca Mattei, Alberto Magi, Romina D'Aurizio, Laura Poliseno   +5 more
wiley   +1 more source