eDiaPredict: an ensemble-based framework for diabetes prediction
Medical systems incorporate modern computational intelligence in healthcare. Machine
learning techniques are applied to predict the onset and reoccurrence of the disease …
learning techniques are applied to predict the onset and reoccurrence of the disease …
Applications and challenges of neural networks in otolaryngology
IA Taciuc, M Dumitru, D Vrinceanu… - Biomedical …, 2024 - spandidos-publications.com
Artificial Intelligence (AI) has become a topic of interest that is frequently debated in all
research fields. The medical field is no exception, where several unanswered questions …
research fields. The medical field is no exception, where several unanswered questions …
Instance reduction for avoiding overfitting in decision trees
Decision trees learning is one of the most practical classification methods in machine
learning, which is used for approximating discrete-valued target functions. However, they …
learning, which is used for approximating discrete-valued target functions. However, they …
Predicting surgical decision-making in vestibular schwannoma using tree-based machine learning
OBJECTIVE Vestibular schwannomas (VSs) are the most common neoplasm of the
cerebellopontine angle in adults. Though these lesions are generally slow growing, their …
cerebellopontine angle in adults. Though these lesions are generally slow growing, their …
Coverage-based classification using association rule mining
Building accurate and compact classifiers in real-world applications is one of the crucial
tasks in data mining nowadays. In this paper, we propose a new method that can reduce the …
tasks in data mining nowadays. In this paper, we propose a new method that can reduce the …
Multi-target-based polypharmacology prediction (mTPP): an approach using virtual screening and machine learning for multi-target drug discovery
K Liu, X Chen, Y Ren, C Liu, T Lv, Y Zhang - Chemico-Biological …, 2022 - Elsevier
Polypharmacology has become a new paradigm in drug discovery and plays an
increasingly vital role in discovering multi-target drugs. In this context, multi-target drugs are …
increasingly vital role in discovering multi-target drugs. In this context, multi-target drugs are …
A precise efficacy determination strategy of traditional Chinese herbs based on Q-markers: Anticancer efficacy of Astragali radix as a case
Y Ren, F Gao, B Li, A Yuan, L Zheng, Y Zhang - Phytomedicine, 2022 - Elsevier
Background As a" multi-components and multi-efficacy" complex system, traditional Chinese
herbs are universally distributed and applied in treating clinical diseases. However, the …
herbs are universally distributed and applied in treating clinical diseases. However, the …
Integrative network modeling highlights the crucial roles of rho-GDI signaling pathway in the progression of non-small cell lung cancer
Non-small cell lung cancer (NSCLC) is the most prevalent form of lung cancer and a leading
cause of cancer-related deaths worldwide. Using an integrative approach, we analyzed a …
cause of cancer-related deaths worldwide. Using an integrative approach, we analyzed a …
A new method for learning decision tree classifier
Z Saurav, MM Mitu, NS Ritu, MA Hasan… - 2023 International …, 2023 - ieeexplore.ieee.org
Decision Tree (DT) induction is one of the popular data modelling techniques that commonly
used in many real-world supervised learning problems. DT is a top-down recursive divide …
used in many real-world supervised learning problems. DT is a top-down recursive divide …
[HTML][HTML] Associations among multimorbid conditions in hospitalized middle-aged and older adults in China: statistical analysis of medical records
Y Zhang, C Chen, L Huang, G Liu… - JMIR Public Health …, 2022 - publichealth.jmir.org
Background Multimorbidity has become a new challenge for medical systems and public
health policy. Understanding the patterns of and associations among multimorbid conditions …
health policy. Understanding the patterns of and associations among multimorbid conditions …