20 citations · 74 across the 13 of their papers we have counts for
6 papers · 1 filter
SmartTriage: A system for personalized patient data capture, documentation generation, and decision support
Ilya Valmianski, Nave Frost, Navdeep Sood +6
Symptom checkers have emerged as an important tool for collecting symptoms and diagnosing patients, minimizing the involvement of clinical personnel. We developed a machine-learnin…
Explaining Natural Language Query Results
Daniel Deutch, Nave Frost, Amir Gilad
Multiple lines of research have developed Natural Language (NL) interfaces for formulating database queries. We build upon this work, but focus on presenting a highly detailed form…
Just in Time: Personal Temporal Insights for Altering Model Decisions
Naama Boer, Daniel Deutch, Nave Frost +1
The interpretability of complex Machine Learning models is coming to be a critical social concern, as they are increasingly used in human-related decision-making processes such as…
T-REx: Table Repair Explanations
Daniel Deutch, Nave Frost, Amir Gilad +1
Data repair is a common and crucial step in many frameworks today, as applications may use data from different sources and of different levels of credibility. Thus, this step has b…
ExKMC: Expanding Explainable -Means Clustering
Nave Frost, Michal Moshkovitz, Cyrus Rashtchian
Despite the popularity of explainable AI, there is limited work on effective methods for unsupervised learning. We study algorithms for -means clustering, focusing on a trade-of…
Explainable -Means and -Medians Clustering
Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz +1
Clustering is a popular form of unsupervised learning for geometric data. Unfortunately, many clustering algorithms lead to cluster assignments that are hard to explain, partially…