Miao Mo

ORCID: 0000-0003-2630-0418
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About
Contact & Profiles
Research Areas
  • AI in cancer detection
  • Radiomics and Machine Learning in Medical Imaging
  • Genital Health and Disease
  • Cytokine Signaling Pathways and Interactions
  • Cervical Cancer and HPV Research
  • Colorectal and Anal Carcinomas
  • Global Cancer Incidence and Screening
  • Financial Distress and Bankruptcy Prediction
  • Stock Market Forecasting Methods
  • Breast Cancer Treatment Studies
  • Urologic and reproductive health conditions
  • Rough Sets and Fuzzy Logic

Xiangya Hospital Central South University
2024

Central South University
2010-2024

Fudan University Shanghai Cancer Center
2021-2022

Shanghai Medical College of Fudan University
2021-2022

Over the recent years, machine learning methods have been increasingly explored in cancer prognosis because of appearance improved algorithms. These algorithms can use censored data for modeling, such as support vector machines survival analysis and random forest (RSF). However, it is still debated whether traditional (Cox proportional hazard regression) or learning-based prognostic models better predictive performance.This study aimed to compare performance breast prediction based on Cox...

10.2196/33440 article EN cc-by JMIR Medical Informatics 2022-01-02

Background: To uncover the potential significance of JAK-STAT-SOCS1 axis in penile cancer, our study was pioneer exploring altered expression processes tumorigenesis, malignant progression and lymphatic metastasis cancer.Methods: In current study, comprehensive analysis cancer analyzed via multiple approaches based on GSE196978 data, single-cell data (6 samples) bulk RNA (7 samples 7 lymph nodes).Results: Our observed an molecular during three different stages from tumorigenesis to...

10.7150/ijms.95490 article EN cc-by-nc International Journal of Medical Sciences 2024-01-01

<sec> <title>BACKGROUND</title> Over the recent years, machine learning methods have been increasingly explored in cancer prognosis because of appearance improved algorithms. These algorithms can use censored data for modeling, such as support vector machines survival analysis and random forest (RSF). However, it is still debated whether traditional (Cox proportional hazard regression) or learning-based prognostic models better predictive performance. </sec> <title>OBJECTIVE</title> This...

10.2196/preprints.33440 preprint EN 2021-09-08
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