Results 131 to 140 of about 475,966 (276)

Plant Disease Detection and Classification: A Systematic Literature Review. [PDF]

Sensors (Basel), 2023
Ramanjot, Mittal U, Wadhawan A, Singla J, Jhanjhi NZ, Ghoniem RM, Ray SK, Abdelmaboud A.   +7 more
europepmc   +1 more source

Perspectives in educating molecular pathologists on liquid biopsy: Toward integrative, equitable, and decentralized precision oncology

Molecular Oncology, EarlyView.
Liquid biopsy enables minimally invasive, real‐time molecular profiling through analysis of circulating biomarkers in biological fluids. This Perspective highlights the importance of training pathologists through integrative educational programs, such as the European Masters in Molecular Pathology, to ensure effective and equitable implementation of ...
Marius Ilié, Umberto Malapelle, Catherine Alix‐Panabières, Claus Lindbjerg Andersen, Sandra Chlebowski, Vivien Lake, Caroline Lacoux, Virginie Lespinet‐Fabre, Olivier Bordone, Simon Heeke, Christophe Bontoux, Ellen Heitzer, Klaus Pantel, Paul Hofman   +13 more
wiley   +1 more source

A New Deep Learning-based Dynamic Paradigm Towards Open-World Plant Disease Detection. [PDF]

Front Plant Sci, 2023
Dong J, Fuentes A, Yoon S, Kim H, Jeong Y, Park DS.   +5 more
europepmc   +1 more source

Management of Phytophthora cinnamomi for biodiversity conservation in Australia: Part 2. National best practice guidelines [PDF]

, 2005
Disease in natural ecosystems of Australia, caused by the introduced plant pathogen Phytophthora cinnamomi, is listed as a key threatening process under the Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act).
Hardy, G.E.St.J., Howard, K., O'Gara, E., Wilson, B.   +3 more
core   +1 more source

Transcriptional network analysis of PTEN‐protein‐deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communication

Molecular Oncology, EarlyView.
Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice, Jose I. Lopez, Aitziber Ugalde‐Olano, Maite Zufiaurre, Ianire Astobiza, Natalia Martin‐Martin, Laura Bozal‐Basterra, Saioa Garcia‐Longarte, Amaia Zabala‐Letona, Sofia Rey, Aida Santos‐Martin, Miguel Unda, Ana Loizaga‐Iriarte, Mariona Graupera, Paolo Nuciforo, Arkaitz Carracedo, Isabel Mendizabal   +16 more
wiley   +1 more source

Exploration of Machine Learning Algorithms and Class Imbalance Handling on Plant Disease Detection

Journal of Applied Informatics and Computing
Plant leaf diseases pose a significant threat to agricultural productivity, necessitating accurate and efficient identification systems for timely intervention.
Ervin Aditya, Ajie Kusuma Wardhana
doaj   +1 more source

Corrigendum: An advanced deep learning models-based plant disease detection: a review of recent research. [PDF]

Front Plant Sci, 2023
Shoaib M, Shah B, Ei-Sappagh S, Ali A, Ullah A, Alenezi F, Gechev T, Hussain T, Ali F.   +8 more
europepmc   +1 more source

Next‐generation proteomics improves lung cancer risk prediction

Molecular Oncology, EarlyView.
This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj, Clara Frick, Ben Schöttker, Bernd Holleczek, Hermann Brenner   +4 more
wiley   +1 more source

Plant disease identification and pesticides recommendation using Dense Net

Cogent Engineering
Plant diseases, mainly caused by bacteria and fungi, affect crop yield and quality. Detecting disease symptoms at an early stage and promptly is a significant obstacle in safeguarding crops. In developing nations, experts and agronomists commonly opt for
Srinu Banothu, Karnam Madhavi, K. M. V. Madan Kumar, Ramesh Gajula, Ch Mallikarjuna Rao, Saurav Dixit, Abhishek Chhetri   +6 more
doaj   +1 more source

Role of Internet of Things and Deep Learning Techniques in Plant Disease Detection and Classification: A Focused Review. [PDF]

Sensors (Basel), 2023
Dhaka VS, Kundu N, Rani G, Zumpano E, Vocaturo E.   +4 more
europepmc   +1 more source