日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Explainable Meta-Learning Ensemble Framework for Predicting Insulin Dose Adjustments in Diabetic Patients: A Comparative Machine Learning Approach with SHAP-Based Clinical Interpretability

可解释元学习集成框架用于预测糖尿病患者胰岛素剂量调整:一种基于SHAP的临床可解释性比较机器学习方法

Guldogan, Emek; Yagin, Burak; Ucuzal, Hasan; Algarni, Abdulmohsen; Al-Hashem, Fahaid; Aghaei, Mohammadreza

Precision Enhanced Bioactivity Prediction of Tyrosine Kinase Inhibitors by Integrating Deep Learning and Molecular Fingerprints Towards Cost-Effective and Targeted Cancer Therapy

通过整合深度学习和分子指纹图谱,精准增强酪氨酸激酶抑制剂的生物活性预测,以实现经济高效的靶向癌症治疗。

Yagin, Fatma Hilal; Gormez, Yasin; Colak, Cemil; Algarni, Abdulmohsen; Al-Hashem, Fahaid; Ardigò, Luca Paolo

The REDOX balance in the prefrontal cortex is positively modulated by aerobic exercise and altered by overfeeding

前额叶皮层的氧化还原平衡受有氧运动的积极调节,并受过度喂养的改变。

Silva, Deyvison Guilherme Martins; de Santana, Jonata Henrique; Bernardo, Elenilson Maximino; de Sousa Fernandes, Matheus Santos; Yagin, Fatma Hilal; Al-Hashem, Fahaid; Fernandes, Mariana P; Fiamoncini, Jarlei; Elkholi, Safaa M; Lagranha, Claudia J

HearteXplain: explainable prediction of acute heart failure and identification of hematologic biomarkers using EBMs and Morris sensitivity analysis

HearteXplain:利用循证医学和Morris敏感性分析对急性心力衰竭进行可解释预测并识别血液学标志物

Yagin, Fatma Hilal; Görmez, Yasin; Algarni, Abdulmohsen; Al-Hashem, Fahaid; Dutta, Ashit Kumar; Aghaei, Mohammadreza

Identification of a Novel Lipidomic Biomarker for Hepatocyte Carcinoma Diagnosis: Advanced Boosting Machine Learning Techniques Integrated with Explainable Artificial Intelligence

肝细胞癌诊断中新型脂质组学生物标志物的鉴定:结合可解释人工智能的先进增强机器学习技术

Yagin, Fatma Hilal; Colak, Cemil; Al-Hashem, Fahaid; Alzakari, Sarah A; Alhussan, Amel Ali; Aghaei, Mohammadreza

Leveraging Explainable Automated Machine Learning (AutoML) and Metabolomics for Robust Diagnosis and Pathophysiological Insights in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

利用可解释的自动化机器学习(AutoML)和代谢组学对肌痛性脑脊髓炎/慢性疲劳综合征(ME/CFS)进行稳健诊断和病理生理学深入了解

Yagin, Fatma Hilal; Colak, Cemil; Al-Hashem, Fahaid; Alzakari, Sarah A; Alhussan, Amel Ali; Aghaei, Mohammadreza

Identifying iNOS and glycogen as biomarkers for degenerated cerebellar purkinje cells in autism spectrum disorder: Protective effects of erythropoietin and zinc sulfate

识别 iNOS 和糖原作为自闭症谱系障碍中退化小脑浦肯野细胞的生物标志物:促红细胞生成素和硫酸锌的保护作用

Abdulaziz M Al-Garni, Sara A Hosny, Faris Almasabi, Ayed A Shati, Norah M Alzamil, Asmaa M ShamsEldeen, Asmaa A El-Shafei, Fahaid Al-Hashem, Hind Zafrah, Amro Maarouf, Bahjat Al-Ani, Ismaeel Bin-Jaliah, Samaa S Kamar

Untargeted Lipidomic Biomarkers for Liver Cancer Diagnosis: A Tree-Based Machine Learning Model Enhanced by Explainable Artificial Intelligence

用于肝癌诊断的非靶向脂质组学生物标志物:基于树的机器学习模型结合可解释人工智能

Colak, Cemil; Yagin, Fatma Hilal; Algarni, Abdulmohsen; Algarni, Ali; Al-Hashem, Fahaid; Ardigò, Luca Paolo

Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis

可解释增强机识别类风湿性关节炎的关键代谢组学生物标志物

Yagin, Fatma Hilal; Colak, Cemil; Algarni, Abdulmohsen; Algarni, Ali; Al-Hashem, Fahaid; Ardigò, Luca Paolo

Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Cancer Detection

提出了一种结合可解释人工智能的综合方法,用于预测血浆样本代谢组学分析中可能用于乳腺癌检测的生物标志物。

Colak, Cemil; Yagin, Fatma Hilal; Algarni, Abdulmohsen; Algarni, Ali; Al-Hashem, Fahaid; Ardigò, Luca Paolo