Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Ali, Alaseem"'
Autor:
Thavavel Vaiyapuri, Prasanalakshmi Balaji, S. Shridevi, Santhi Muttipoll Dharmarajlu, Nourah Ali AlAseem
Publikováno v:
AIMS Mathematics, Vol 9, Iss 6, Pp 16704-16720 (2024)
Bone cancer detection is an essential region of medical analysis but developments in medical imaging and artificial intelligence (AI) are vital. Using approaches, namely deep learning (DL) and machine learning (ML), radiologists and medical staff can
Externí odkaz:
https://doaj.org/article/f3efb7d8f0f044d58c09774b7c1f83df
Autor:
Fahdah A Almarshad, Prasanalakshmi Balaji, Liyakathunisa Syed, Eman Aljohani, Santhi Muttipoll Dharmarajlu, Thavavel Vaiyapuri, Nourah Ali AlAseem
Publikováno v:
IEEE Access, Vol 12, Pp 137237-137246 (2024)
Gastrointestinal or gastric cancer (GC) classification is a serious field of medical research and healthcare technology, where innovative machine learning (ML) and deep learning (DL) models are employed to categorize and analyze many kinds of GCs lik
Externí odkaz:
https://doaj.org/article/418b152f1f114f0e81b0dbb0f8eeab5d
Autor:
Jehad A. Aldali, Badi A. Alotaibi, Hamzah J. Aldali, Glowi A. Alasiri, Ali Alaseem, Abdulaziz M. Almuqrin, Abdulrahman Alshalani, Fahad T. Alotaibi
Publikováno v:
Biomedicines, Vol 11, Iss 8, p 2203 (2023)
The coronavirus disease 2019 (COVID-19) vaccines have been developed to help prevent the spread of the virus infections. The COVID-19 vaccines, including Pfizer, Moderna, and AstraZeneca, have undergone rigorous testing and have demonstrated both saf
Externí odkaz:
https://doaj.org/article/36019218197f4822a91b638baf60896f
Autor:
Mohammad, Algahtani, Umamaheswari, Natarajan, Khalid, Alhazzani, Ali, Alaseem, Appu, Rathinavelu
Publikováno v:
Cancer Genetics. :71-89
Glioblastoma Multiforme (GBM) is one of the most aggressive and lethal types of all cancers, with an average 5-year survival rate of 5%. Since GBM tumors are highly vascularized tumors, and their growth is angiogenesis-dependent, antagonizing tumor a
Autor:
Khalid Alhazzani, Thiagarajan Venkatesan, Umamaheswari Natarajan, Mohammad Algahtani, Ali Alaseem, Saad Alobid, Appu Rathinavelu
Publikováno v:
Biotechnology Letters. 44:787-801
Colorectal cancer (CRC) is the third most prevalent type of cancer in the United States. The treatment options for cancer include surgery, chemotherapy, radiation, and/or targeted therapy, which show significant improvement in overall survival. Among
Autor:
Thiagarajan Venkatesan, Ali Alaseem, Aiyavu Chinnaiyan, Sivanesan Dhandayuthapani, Thanigaivelan Kanagasabai, Khalid Alhazzani, Priya Dondapati, Saad Alobid, Umamaheswari Natarajan, Ruben Schwartz, Appu Rathinavelu
Publikováno v:
Cells, Vol 7, Iss 5, p 41 (2018)
The Murine Double Minute 2 (MDM2) amplification or overexpression has been found in many tumors with high metastatic and angiogenic ability. Our experiments were designed to explore the impact of MDM2 overexpression, specifically on the levels of ang
Externí odkaz:
https://doaj.org/article/b32d1e9cf99540b493245b2f3bda1b17
Autor:
Ali Alaseem, Arkene Levy, Saad Alobid, Keerthi Thallapureddy, Appu Rathinavelu, Priya Dondapati, Khalid Alhazzani, Paramajot Kaur, Khadijah Cheema
Publikováno v:
Current Cancer Drug Targets. 19:179-188
Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase, which is an essential player in regulating cell migration, invasion, adhesion, proliferation, and survival. Its overexpression and activation have been identified in sixty-eight percent o
Publikováno v:
International Journal of Advanced Computer Science and Applications. 12
In recent years, the Industrial Internet of things (IIoT) is a fastest advancing innovative technology with a poten-tial to digitize and interconnect many industries for huge business opportunities and development of global GDP. IIoT is used in diver
Autor:
Sivanesan Dhandayuthapani, Thiagarajan Venkatesan, Ali Alaseem, Khalid Alhazzani, Appu Rathinavelu, Mohammad Algahtani
Publikováno v:
Anti-Angiogenesis Drug Discovery and Development
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7be2547e14253831762fc75ec9f76280
https://doi.org/10.2174/9781681083971119040005
https://doi.org/10.2174/9781681083971119040005
Publikováno v:
Sensors (Basel, Switzerland)
Sensors
Volume 19
Issue 6
Sensors, Vol 19, Iss 6, p 1265 (2019)
Sensors
Volume 19
Issue 6
Sensors, Vol 19, Iss 6, p 1265 (2019)
Detection of abnormalities in wireless capsule endoscopy (WCE) images is a challenging task. Typically, these images suffer from low contrast, complex background, variations in lesion shape and color, which affect the accuracy of their segmentation a