Development of a Novel Machine Learning Algorithm to Monitor Vascular Tissue Transfers Using Speech Recognition Techniques
ISEF · 2014 Earth and Environmental Sciences First Award
Overview
A pencil doppler is the primary tool used in detection of devastating vascular tissue transfer-related ailments through analysis of vascular flow. However, the doppler is ineffective because of a manual, time-consuming interface. The goal of this study was to construct a machine-learning system, with the ability to automatically detect and classify audio emitted from the doppler as either normal or abnormal. Data collected from various doppler devices was labeled using Waveform, and down-sampled in Python. The frequency vectors from each data sample were categorized onto a time-frequency and separated into our labels. Viterbi segmentation was applied to the HMM to identify paths with the highest probability of reaching an end state. A contingency table was calculated to determine the effectiveness of the algorithm, and the statistical significance of the diagnoses. Our research resulted in a 95.6% detection rate with a p = .044 significance. This diagnostic system can potentially increase efficiency in medical centers and decrease tissue failures resulting from late diagnosis.
Awards (1)
- First Award of $5,000 $5,000
Competition history
- ISEF 2014
Resources
Related projects
ISEF · 2017
Accurate, Low-Cost Diagnosis and Monitoring of Parkinson's Disease by Detecting Dysphonic Features through a Machine-Learning Algorithm
CSEF · 2017
Accurate, Low-Cost Diagnosis of Parkinson's Disease by Detecting Dysphonic Features through a Machine-Learning Algorithm
CSEF · 2017
A Machine Learning Approach for the Diagnosis of Parkinson's Disease via Speech Analysis
ISEF · 2022
Enabling Ankle-Brachial Index Prediction From Dopplers Using Deep Learning for Peripheral Arterial Disease Diagnosis
JSHS · 2023
Enabling Ankle-Brachial Index Prediction from Doppler’s Using Deep Learning for Peripheral Arterial Disease Diagnosis
CSEF · 2015
Signal-Processing Driven Machine Learning Algorithms for Parkinson's Progression and Tremor-Based Disease Diagnostics
ISEF · 2021
Diagnosing and Classifying Aphasia: Employing Deep Learning to Accelerate Recovery in Aphasic Stroke Victims
ISEF · 2026
NeuroAcoustix: Revolutionizing Brain Health Through Sound
Closest projects by meaning, across every fair and year in the corpus.
Browse more like this
Source: Regeneron International Science and Engineering Fair