An overview on the advancements of support vector machine models in healthcare applications: a review
R Guido, S Ferrisi, D Lofaro, D Conforti - Information, 2024 - mdpi.com
Support vector machines (SVMs) are well-known machine learning algorithms for
classification and regression applications. In the healthcare domain, they have been used …
classification and regression applications. In the healthcare domain, they have been used …
Emerging applications of machine learning in genomic medicine and healthcare
The integration of artificial intelligence technologies has propelled the progress of clinical
and genomic medicine in recent years. The significant increase in computing power has …
and genomic medicine in recent years. The significant increase in computing power has …
Raman spectroscopy and machine learning for the classification of breast cancers
L Zhang, C Li, D Peng, X Yi, S He, F Liu… - … Acta Part A: Molecular …, 2022 - Elsevier
Breast cancer is a major health threat for women. The drug responses associated with
different breast cancer subtypes have obvious effects on therapeutic outcomes; therefore …
different breast cancer subtypes have obvious effects on therapeutic outcomes; therefore …
Diffused responsibility: attributions of responsibility in the use of AI-driven clinical decision support systems
Good decision-making is a complex endeavor, and particularly so in a health context. The
possibilities for day-to-day clinical practice opened up by AI-driven clinical decision support …
possibilities for day-to-day clinical practice opened up by AI-driven clinical decision support …
Predicting groundwater level using traditional and deep machine learning algorithms
F Feng, H Ghorbani, AE Radwan - Frontiers in Environmental Science, 2024 - frontiersin.org
This research aims to evaluate various traditional or deep machine learning algorithms for
the prediction of groundwater level (GWL) using three key input variables specific to Izeh …
the prediction of groundwater level (GWL) using three key input variables specific to Izeh …
Advances in machine learning-assisted SERS sensing towards food safety and biomedical analysis
Surface-enhanced Raman scattering, has extensive applications in the fields of medicine
and food due to its high-sensitivity, speed, non-destructive nature, and cost-effectiveness …
and food due to its high-sensitivity, speed, non-destructive nature, and cost-effectiveness …
Application of serum SERS technology based on thermally annealed silver nanoparticle composite substrate in breast cancer
Z Cheng, H Li, C Chen, X Lv, EG Zuo, X ** in Tehri region, Garhwal Himalaya
S Saha, A Saha, TK Hembram, B Kundu… - Geocarto …, 2022 - Taylor & Francis
Over the years, landslide has become one of the most destructive events that can happen in
hilly areas. Tehri, a region in the Himalayas is no different. Current research aids in the …
hilly areas. Tehri, a region in the Himalayas is no different. Current research aids in the …
Molecular characterization and landscape of breast cancer models from a multi-omics perspective
MMO Ortiz, ER Andrechek - Journal of mammary gland biology and …, 2023 - Springer
Breast cancer is well-known to be a highly heterogenous disease. This facet of cancer
makes finding a research model that mirrors the disparate intrinsic features challenging …
makes finding a research model that mirrors the disparate intrinsic features challenging …
Raman spectroscopy and machine learning for the classification of esophageal squamous carcinoma
W Huang, Q Shang, X **ao, H Zhang, Y Gu… - … Acta Part A: Molecular …, 2022 - Elsevier
Early diagnosis of esophageal squamous cell carcinoma (ESCC), a common malignant
tumor with a low overall survival rate due to metastasis and recurrence, is critical for effective …
tumor with a low overall survival rate due to metastasis and recurrence, is critical for effective …