Succinct Differentiation of Disparate Boosting Ensemble Learning Methods for Prognostication of Polycystic Ovary Syndrome Diagnosis

Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification

The polycystic ovary syndrome diagnosis is a problem that can be leveraged using prognostication based learning procedures. Many implementations of PCOS can be seen with Machine Learning but the algorithms have certain limitations in utilizing the processing power graphical processing units. The simple machine learning algorithms can be improved with advanced frameworks using Deep Learning. The Linear Discriminant Analysis is a linear dimensionality reduction algorithm for classification that can be boosted in terms of performance using deep learning with Deep LDA, a transformed version of the…

Discriminant Analysis in Contrasting Dimensions for Polycystic Ovary Syndrome Prognostication

A lot of prognostication methodologies have been formulated for early detection of Polycystic Ovary Syndrome also known as PCOS using Machine Learning. PCOS is a binary classification problem. Dimensionality Reduction methods impact the performance of Machine Learning to a greater extent and using a Supervised Dimensionality Reduction method can give us a new edge to tackle this problem. In this paper we present Discriminant Analysis in different dimensions with Linear and Quadratic form for binary classification along with metrics. We were able to achieve good accuracy and less variation with…

面向患者数据的联邦学习用于隐私保护的多囊卵巢综合征治疗

Federated Learning on Patient Data for Privacy-Protecting Polycystic Ovary Syndrome Treatment

针对多囊卵巢综合征研究受患者数据隐私与匮乏限制的问题，本研究探索联邦学习在预测该病最优药物中的应用，验证多种联邦学习方法在合成数据集上的有效性，为兼顾数据利用与患者隐私保护提供方案。

PCONet: A Convolutional Neural Network Architecture to Detect Polycystic Ovary Syndrome (PCOS) from Ovarian Ultrasound Images

Polycystic Ovary Syndrome (PCOS) is an endrocrinological dysfunction prevalent among women of reproductive age. PCOS is a combination of syndromes caused by an excess of androgens - a group of sex hormones - in women. Syndromes including acne, alopecia, hirsutism, hyperandrogenaemia, oligo-ovulation, etc. are caused by PCOS. It is also a major cause of female infertility. An estimated 15% of reproductive-aged women are affected by PCOS globally. The necessity of detecting PCOS early due to the severity of its deleterious effects cannot be overstated. In this paper, we have developed PCONet - a…

使用机器学习方法对多囊卵巢综合征（PCOS）的诊断研究

Investigation of Polycystic Ovary Syndrome (PCOS) Diagnosis Using Machine Learning Approaches

研究利用机器学习方法结合独特特征选择算法预测多囊卵巢综合征，介绍结合特征工程和机器学习的数据驱动方法，经多种特征选择方法训练模型，结果显示经随机森林特征重要性和最高相关性选择十个特征的AdaBoost测试准确率最高。

Binary Classification for High Dimensional Data using Supervised Non-Parametric Ensemble Method

High dimensional data for classification does create many difficulties for machine learning algorithms. The generalization can be done using ensemble learning methods such as bagging based supervised non-parametric random forest algorithm. In this paper we solve the problem of binary classification for high dimensional data using random forest for polycystic ovary syndrome dataset. We have performed the implementation and provided a detailed visualization of the data for general inference. The training accuracy that we have achieved is 95.6% and validation accuracy over 91.74% respectively.