Results 31 to 40 of about 15,233 (135)

Types of Pain in Multiple System Atrophy

Movement Disorders, EarlyView.
Abstract Background Pain affects up to 87% of people with multiple system atrophy (MSA), but it remains unclear which types of pain contribute most to the overall burden. Objective To estimate the frequency of different types of pain in MSA individuals.
Nicole Campese, Mubasher A. Qamar, Maria Alexandra Chiriac, Georg Göbel, Julia Wanschitz, Andreas Schlager, Bianca Caliò, Fabian Leys, Pam Bower, Laura Zamarian, Anette Schrag, Roy Freeman, Horacio Kaufmann, Roberta Granata, Stefan Kiechl, Werner Poewe, Klaus Seppi, Gregor Wenning, K. Ray Chaudhuri, Alessandra Fanciulli   +19 more
wiley   +1 more source

Targeting human apurinic/apyrimidinic endonuclease 1 (APE1) in phosphatase and tensin homolog (PTEN) deficient melanoma cells for personalized therapy [PDF]

, 2014
Phosphatase and tensin homolog (PTEN) loss is associated with genomic instability. APE1 is a key player in DNA base excision repair (BER) and an emerging drug target in cancer.
Allinson, Ashworth, Ashworth, Bertram, Bosenberg, Botti, Bristow, Burma, Campisi, Curtin, Eng, Eng, Foiani, Gerson, He, Helleday, Hickson, Kelley, Larue, Li, Madhusudan, Madhusudan, Madhusudan, Madhusudan, Maloney, Maloney, Meyskens, Newton-Bishop, Pandolfi, Pandolfi, Parsons, Polyak, Pu, Reis-Filho, Reis-Filho, Ribas, Rimm, Robertson, Rocha, Simeonov, Simeonov, Smalley, Stambolic, Stambolic, Teo, Wadhwa, Wilson, Wilson, Yin, Zhang   +49 more
core   +2 more sources

Semi‐Automatic Assessment of Crohn's Disease Activity by Combined Analysis of Bowel Lesions and Creeping Fat

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop and evaluate Crohn‐BOOST, an open‐source tool enabling semi‐automatic segmentation of intestinal lesions and creeping fat on magnetic resonance enterography (MR Enterography), and to assess whether quantitative metrics derived from these segmentations relate to radiological disease activity scored with simplified MaRIA ...
Antoine Kneib, Astrée Lemore, Gabriela Hossu, Laurent Peyrin‐Biroulet, Valérie Laurent, Freddy Odille   +5 more
wiley   +1 more source

What practicing pathologists and oncologists should know about the new computational pathology‐based companion diagnostic tools

The Journal of Pathology, EarlyView.
Abstract The integration of artificial intelligence into pathology is transforming the assessment of histological and immunohistochemical (IHC) slides, offering opportunities to reduce variability and streamline diagnostics. In practical terms, most available tools and research models emulate the diagnostic capabilities of pathologists by detecting ...
Diana Montezuma, Sara P. Oliveira, Inti Zlobec, Nadieh Khalili, Jordi Temprana‐Salvador, Sabine Leh, David Ameisen, Mircea‐Sebastian Șerbănescu, Arsela Prelaj, Jakob Nikolas Kather, Norman Zerbe, Vincenzo L'Imperio   +11 more
wiley   +1 more source

Outlook Magazine, Summer 2018 [PDF]

, 2018
https://digitalcommons.wustl.edu/outlook/1204/thumbnail ...

core   +1 more source

Cross-Modal Data Programming Enables Rapid Medical Machine Learning

, 2019
Labeling training datasets has become a key barrier to building medical machine learning models. One strategy is to generate training labels programmatically, for example by applying natural language processing pipelines to text reports associated with ...
Dunnmon, Jared, Goldman, Roger, Khandwala, Nishith, Lee-Messer, Christopher, Lungren, Matthew, Markert, Matthew, Ratner, Alexander, Rubin, Daniel, Ré, Christopher, Saab, Khaled, Sagreiya, Hersh   +10 more
core   +1 more source

Early Detection of Lower Adherence to Long‐Term e‐Diary Recording: A Checkpoint to Target Early Educational Intervention in Seasonal Allergic Rhinitis?

Clinical &Experimental Allergy, EarlyView.
Adherence to e‐Diary reporting was investigated in a blended care setting among pollen allergic patients with heterogeneous cultural backgrounds. A stable ‘higher’ and a more variable ‘lower’ adherence cluster were identified. Early identification of lower adherence is possible and might inform early interventions to improve patient adherence. ABSTRACT
S. Dramburg, C. J. Hernandez Toro, U. Grittner, S. Tripodi, S. Arasi, A. Acar Şahin, X. Aggelidis, A. Barbalace, A. Bourgoin, B. Bregu, M. A. Brighetti, E. Caeiro, S. Caglayan Sozmen, L. Caminiti, D. Charpin, M. Couto, L. Delgado, A. Di Rienzo Businco, C. Dimier, M. V. Dimou, J. A. Fonseca, O. Goksel, D. Hernandez, T. M. Hoffmann, D. T. Jang, F. Kalpaklioglu, B. Lame, R. Llusar, M. Makris, A. Mazon, E. Mesonjesi, A. Nieto, A. Öztürk, L. Pahus, G. Pajno, I. Panasiti, N. G. Papadopoulos, E. Pellegrini, S. Pelosi, A. M. Pereira, M. Pereira, N. M. Pinar, E. Potapova, A. Priftanji, F. Psarros, C. Sackesen, I. Sfika, J. Suarez, M. Thibaudon, A. Travaglini, U. Uguz, V. Verdier, V. Villella, P. Xepapadaki, D. Yazici, P. M. Matricardi   +55 more
wiley   +1 more source

Outlook Magazine, Spring 2014 [PDF]

, 2014
https://digitalcommons.wustl.edu/outlook/1192/thumbnail ...

core   +1 more source

Healthcare Professionals' Perceptions of Artificial Intelligence in Healthcare—A Systematic Review of Qualitative Studies

Journal of Advanced Nursing, EarlyView.
ABSTRACT Aim To identify the experiences and perceptions of healthcare professionals on artificial intelligence in healthcare. Design Systematic literature review of qualitative studies and meta‐aggregation. Data Sources CINAHL, PubMed, Scopus, Medic and ProQuest were systematically searched on December 9, 2024. Results Twenty‐six studies were included
Huotari Sini, Mikkonen Kristina, Jarva Erika, Suonnansalo Petra, Kaikkonen Assi, Lee Jay Jung Jae, Oikarinen Anne   +6 more
wiley   +1 more source

Saliency-driven system models for cell analysis with deep learning. [PDF]

, 2019
Background and objectivesSaliency refers to the visual perception quality that makes objects in a scene to stand out from others and attract attention.
Bianchi, Andrea GC, Carneiro, Cláudia M, Ferreira, Daniel S, Medeiros, Fátima NS, Ramalho, Geraldo LB, Rezende, Mariana T, Tobias, Alessandra HG, Torres, Débora, Ushizima, Daniela M   +8 more
core   +2 more sources