Prashanti Manda

A multi-modal machine learning approach towards predicting patient readmission

This paper develops and compares machine learning models to predict 30-day unplanned readmission in frail elderly patients using electronic health records.

Taking a Dive: Experiments in Deep Learning for Automatic Ontology-based Annotation of Scientific Literature

This study develops a GRU-based deep learning model for ontology-based annotation of scientific literature, achieving high precision and recall across five ontologies.

An analysis and comparison of the statistical sensitivity of semantic similarity metrics

The paper compares the statistical sensitivity of five semantic similarity metrics and four aggregation methods for biological objects, finding that Resnik similarity and Groupwise aggregation perform best.

Annotation of phenotypes using ontologies: a Gold Standard for the training and evaluation of natural language processing systems

The paper introduces a Gold Standard corpus for ontology-based phenotype annotation and evaluates a tool's performance against human annotations.

Measuring the importance of annotation granularity to the detection of semantic similarity between phenotype profiles

This study evaluates how varying levels of annotation granularity affect semantic similarity metrics in phenotype profiles, finding that coarse annotations may suffice for detecting significant similarity.

Investigating the importance of anatomical homology for cross-species phenotype comparisons using semantic similarity.

This study examines how including homology axioms affects semantic similarity between orthologous and non-orthologous gene pairs across human, mouse, and zebrafish species.

Using the Phenoscape Knowledgebase to relate genetic perturbations to phenotypic evolution

The paper demonstrates how the Phenoscape Knowledgebase links genetic perturbations to phenotypic evolution by comparing phenotypic profiles across species.