Improvement in automated diagnosis of soft tissues tumors using machine learning

Classification of Soft Tissue Tumors by Machine Learning Algorithms

Automated ECG Delineation using Machine Learning Algorithms

The aim of automated electrocardiogram (ECG) delineation system is the reliable detection of fundamental ECG components and from these fundamental measurements, the parameters of diagnostic significance, namely, P-duration, PR-interval, QRS-duration, QTinterval, are to be identified and extracted. In this work, two supervised machine learning algorithms, K-Nearest neighbour (KNN) and Support Ve...

Automated Options Trading Using Machine Learning

We summarize an experimental study on the viability of several call option trading strategies that rely on our earlier work with machine-learning-based detection and prediction of heightened volatility periods. The proposed trading strategies makes use of the connection between call options prices and volatility in the underlying.1,2 As part of these strategies, the trader would purchase call o...

Automated Essay Grading Using Machine Learning

The project aims to build an automated essay scoring system using a data set of ≈13000 essays from kaggle.com. These essays were divided into 8 di erent sets based on context. We extracted features such as total word count per essay, sentence count, number of long words, part of speech counts etc from the training set essays. We used a linear regression model to learn from these features and ge...

Automated Walks using Machine Learning for Segmentation

This paper describes an automated algorithm for segmentation of brain structures (CSF, white matter, and gray matter) in MR images. We employ machine learning (using k -Nearest Neighbors) of features derived from k -means, Canny edge detection, and Tourist Walks to fully automate the seeding process of the Random Walker algorithm. We test our methods on the MRBrainS13 dataset, which consists of...