Avi Rosenfeld

Jerusalem College of Technology | JCT · Department of Computer Science

This paper presents objective metrics for how explainable artificial intelligence (XAI) can be quantified. Through an overview of current trends, we show that many explanations are generated post-hoc and independent of the agent's logical process, which in turn creates explanations with limited meaning as they lack transparency and fidelity. While...

Introduction The SPIT study (ISRCTN11921553) aims to investigate the methylation changes in saliva that result from Crohn’s disease with the ultimate aim of developing a diagnostic biomarker. Aims and Methods We selected 192 volunteers, 96 with Crohn’s Disease and 96 controls. These were drawn from participants in the SPIT study and were carefully...

Introduction The SPIT study aims to investigate the methylation changes in saliva that result from oesophagael cancer with the ultimate aim of developing a diagnostic biomarker. Methods We recruited volunteers with adenocarcinoma, intramucosal carcinoma, Barrett’s Oesophagus and High-Grade Dysplasia. We also recruited two distinct classes of contr...

Introduction Waiting times for endoscopy are rising rapidly following the COVID-19 pandemic. In addition, cancers may be missed as patients are placed on routine waiting lists but not monitored. Some hospitals use the Edinburgh Dysphagia Score to assess and prioritise patients for investigation. This offers a sensitivity of 98.4% and specificity of...

Gleason score 7 prostate cancer with a higher proportion of pattern 4 (G4) has been linked to genomic heterogeneity and poorer patient outcome. The current assessment of G4 proportion uses estimation by a pathologist, with a higher proportion of G4 more likely to trigger additional imaging and treatment over active surveillance. This estimation met...

This paper presents a survey of issues relating to explainability in Human-Agent Systems. We consider fundamental questions about the Why, Who, What, When and How of explainability. First, we define explainability and its relationship to the related terms of interpretability, transparency, explicitness, and faithfulness. These definitions allow us...

BACKGROUND: Screening for Barrett's oesophagus relies on endoscopy, which is invasive and few who undergo the procedure are found to have the condition. We aimed to use machine learning techniques to develop and externally validate a simple risk prediction panel to screen individuals for Barrett's oesophagus. METHODS: In this prospective study, mac...

Background: Screening for Barrett's Oesophagus (BE) relies on endoscopy which is invasive and has a low yield. This study aimed to develop and externally validate a simple symptom and risk-factor questionnaire to screen for patients with BE. Methods: Questionnaires from 1299 patients in the BEST2 case-controlled study were analysed: 880 had BE i...

This paper presents a taxonomy of explainability in human–agent systems. We consider fundamental questions about the Why, Who, What, When and How of explainability. First, we define explainability, and its relationship to the related terms of interpretability, transparency, explicitness, and faithfulness. These definitions allow us to answer why ex...

Introduction Barrett’s oesophagus (BO) is the only known precursor of esophageal adenocarcinoma. The current gold-standard test for diagnosing BO is endoscopy which is expensive and impractical as a population screening tool. We aimed to develop a robust questionnaire that could be used in routine clinical practice to identify patients with differe...

This paper presents a taxonomy of explainability in Human-Agent Systems. We consider fundamental questions about the Why, Who, What, When and How of explainability. First, we define explainability, and its relationship to the related terms of interpretability, transparency, explicitness, and faithfulness. These definitions allow us to answer why ex...

This paper presents a taxonomy of explainability in Human-Agent Systems. We consider fundamental questions about the Why, Who, What, When and How of explainability. First, we define explainability, and its relationship to the related terms of interpretability, transparency, explicitness, and faithfulness. These definitions allow us to answer why ex...

Designers of robotic groups are faced with the formidable task of creating effective coordination architectures that can deal with collisions due to changing environment conditions and hardware failures. Communication between robots is a mechanism that can at times be helpful in such systems, but can also create a time, energy, or computation overh...

BACKGROUND Social networks on the Internet have become ubiquitous applications that allow people to easily share text, pictures, and audio and video files. Popular networks include WhatsApp, Facebook, Reddit, and LinkedIn. OBJECTIVE We present an extensive study of the usage of the WhatsApp social network, an Internet messaging application that is...

Introduction Barrett's oesophagus (BE) is a precursor to oesophageal adenocarcinoma (OAC). Endoscopic surveillance is performed to detect dysplasia arising in BE as it is likely to be amenable to curative treatment. At present, there are no guidelines on who should perform surveillance endoscopy in BE. Machine learning (ML) is a branch of artificia...

Introduction: A "Negative" ureteroscopy (URS) is defined as a URS in which no stone is found during the procedure. It may occur when the stone has already been passed spontaneously or when it is located outside the collecting system. The aim of the study was to outline risk factors for Negative-URS. Materials and methods: We retrospectively anal...

Internet social networks have become a ubiquitous application allowing people to easily share text, pictures, and audio and video files. Popular networks include WhatsApp, Facebook, Reddit and LinkedIn. We present an extensive study of the usage of the WhatsApp social network, an Internet messaging application that is quickly replacing SMS messagin...

To date, attribute discretization is typically performed by replacing the original set of continuous features with a transposed set of discrete ones. This paper provides support for a new idea that discretized features should often be used in addition to existing features and as such, datasets should be extended, and not replaced, by discretization...

Text Classification (TC) is the task of automatically assigning documents to a fixed number of categories. TC is an important component in many text applications such as text indexing, information extraction, information retrieval, text mining, and word sense disambiguation. In this paper, we present an alternative method of feature reduction - a c...

Robots are being deployed in an increasing variety of environments for longer periods of time. As the number of robots grows, they will increasingly need to interact with other robots. Additionally, the number of companies and research laboratories producing these robots is increasing, leading to the situation where these robots may not share a com...

Introduction Barrett’s Oesophagus (BE) is the pre-cursor to oesophageal adenocarcinoma. Endoscopic surveillance is performed to detect dysplasia in BE as it is likely to be treatable. Machine Learning (ML) is a technology that generates simple rules, known as a Decision Tree (DT). Using a DT generated from Expert Endoscopists (EE), we hypothesised...

This paper presents an extensive study of the usage of the WhatsApp social network, an Internet messaging application that is quickly replacing SMS messaging. It is based on the analysis of over 4 million messages from nearly 100 users that we collected in order to understand people's use of the network. We believe that this is the first in-depth s...

The use of data mining has led to many significant medical discoveries. However, many challenges still exist in using these methods for knowledge discovery within this field given that the large amounts of data medical practitioners collect often creates a curse of dimensionality. To address this challenge, attribute selection approaches have been...

An important area of social network research is identifying missing information which is not visible or explicitly represented in the network. Recently, the missing node identification problem was introduced where missing members in the social network structure must be identified. However, previous works did not consider the possibility that inform...

Negotiation between virtual agents and humans is a complex field that requires designers of systems to be aware not only of the efficient solutions to a given game, but also the mechanisms by which humans create value over multiple negotiations. One way of considering the agent's impact beyond a single negotiation session is by considering the use...

Autonomous agents developed by experts are embedded with the capability to interact well with people from different cultures. When designing expert agents intended to interact with autonomous agents developed by non-game theory agents (NGTE), it is beneficial to obtain insights on the behavior of these NGTE agents. Is the behavior of these NGTE age...

To date, a variety of automated negotiation agents have been created. While each of these agents has been shown to be effective in negotiating with people in specific environments, they typically lack the natural language processing support required to enable real-world types of interactions. To address this limitation, we present NegoChat-A, an ag...

We consider the problem of task allocation in crowdsourcing systems with multiple complex workflows, each of which consists of a set of inter-dependent micro-tasks.We propose Budgeteer, an algorithm to solve this problem under a budget constraint. In particular, our algorithm first calculates an efficient way to allocate budget to each workflow. It...

This paper represents a paradigm shift in what advice agents should provide people. Contrary to what was previously thought, we empirically show that agents that dispense optimal advice will not necessary facilitate the best improvement in people's strategies. Instead, we claim that agents should at times suboptimally advise. We provide results dem...

An important area of social network research is identifying missing information which is not explicitly represented in the network or is not visible to all. In this paper, we propose a novel Hybrid Approach of Classifier and Clustering,a which we refer to as HACC, to solve the missing node identification problem in social networks. HACC utilizes a...

This paper represents a paradigm shift in what advice agents should provide people. Contrary to what was previously thought, we empirically show that agents that dispense optimal advice will not necessary facilitate the best improvement in people's strategies. Instead, we claim that agents should at times suboptimally advise. We provide results dem...

To date, a variety of automated negotiation agents have been created. While each of these agents has been shown to be effective in negotiating with people in specific environments, they lack natural language processing (NLP) methods required to enable real-world types of interactions. In this paper we study how existing agents must be modified to a...

We consider the problem of task allocation in crowdsourcing systems with multiple complex workflows, each of which consists of a set of interdependent micro-tasks. We propose Budgeteer, an algorithm to solve this problem under a budget constraint. In particular, our algorithm first calculates an efficient way to allocate budget to each workflow. It...

Adaptive Cruise Control (ACC) is a technology that allows a vehi-cle to automatically adjust its speed to maintain a preset distance from the vehicle in front of it based on the driver's preferences. In-dividual drivers have different driving styles and preferences. Cur-rent systems do not distinguish among the users. We introduce a method to combi...

Introduction Barrett’s oesophagus (BE) is the pre-cursor for oesophageal adenocarcinoma. Endoscopic surveillance is performed to detect dysplasia in BE as it is likely to be amenable to curative treatment. Current surveillance relies on white-light endoscopy to obtain 4-quadrant biopsies through every 2cm of the BE segment. This samples less than 5...

In this paper we explore how data mining can be applied to gastroenterology, and specifically to aid in the diagnosis of patients with high-risk lesions within Barrett's oesophagus (BE). BE is the only identifiable premalignant lesion for oesophageal adenocarcinoma (OA), a tumor whose incidence has been rising rapidly in the Western World.This pape...

To date, a variety of automated negotiation agents have been cre-ated. While each of these agents has been shown to be effective in negotiating with people in specific environments, they lack natu-ral language processing support required to enable real-world types of interactions. In this paper we present NegoChat, the first nego-tiation agent that...

Interruptions can have a significant impact on users working to complete a task. When people are collaborating, either with other users or with systems, coordinating interruptions is an important factor in maintaining efficiency and preventing information overload. Computer systems can observe user behavior, model it, and use this to optimize the i...

Corruption frequently occurs in many aspects of multi-party interaction between private agencies and government employees. Past works studying corruption in a lab context have explicitly included covert or illegal activities in participants’ strategy space or have relied on surveys like the Corruption Perception Index (CPI). This paper studies corr...

In the last decade, scenario-based serious-games have become a main tool for learning new skills and capabilities. An important factor in the development of such systems is the overhead in time, cost and human resources to manually create the content for these scenarios. We focus on how to create content for scenarios in medical, military, commerce...

Agents that interact with humans are known to benefit from modeling them. Therefore, when designing agents intended for interaction with automated agents, it is crucial to model the other agents. However, little is known about how to model automated agents and in particular non-expert agents. Are automated agents to be modeled the same way that an...

Scenario-based serious-games have become an important tool for teaching new skills and capabilities. An important factor in the development of such systems is reducing the time and cost overheads in manually creating content for these scenarios. To address this challenge, we present Scenario-Gen, an automatic method for generating content about eve...

Crowdsourcing is a multi-agent task allocation paradigm that involves up to millions of workers, of varying reliability and availability, performing large numbers of micro-tasks. A key challenge is to crowdsource, at minimal cost and with predictable accuracy, complex tasks that involve different types of interdependent micro-tasks structured into...

This paper analyzes what stylistic characteristics differentiate different styles of writing, and specifically types of different A-level computer science articles. To do so, we compared various full papers using stylistic feature sets and a supervised machine learning method. We report on the success of this approach in identifying papers from the...

Embedding planning systems in real-world domains has led to the necessity of Distributed Continual Planning (DCP) systems where planning activities are distributed across multiple agents and plan generation may occur concurrently with plan execution. A key challenge in DCP systems is how to coordinate activities for a group of planning agents. This...

An important area of social networks research is identifying missing information which is not explicitly represented in the network, or is not visible to all. Recently, the Missing Node Identification problem was introduced where missing members in the social network structure must be identified. However, previous works did not consider the possibi...

While great strides have been made in multiagent teamwork, existing approaches typically assume extensive information exists about teammates and how to coordinate actions. This paper addresses how robust teamwork can still be created even if limited or no information exists about a specific group of teammates, as in the ad hoc teamwork scenario. Th...

In recent years, social networks have surged in popularity. One key aspect of social network research is identifying important missing information that is not explicitly represented in the network, or is not visible to all. To date, this line of research typically focused on finding the connections that are missing between nodes, a challenge typica...

In this paper we investigate methods for selecting the best algorithms in classic distributed constraint optimization problems. While these are NP-complete problems, many heuristics have nonetheless been proposed. We found that the best method to use can change radically based on the specifics of a given problem instance. Thus, dynamic methods are...

In this paper we present SNACS, a novel method for creating Social Narratives that can be Adapted using information from Crowdsourcing. Previous methods for automatic narrative generation require that the primary author explicitly detail nearly all parts of the story, including details about the narrative. This is also the case for narratives withi...

Recommender systems are now an integral part of many e-commerce websites, providing people relevant products they should consider purchasing. To date, many types of recommender systems have been proposed, with major categories belonging to item-based, user-based (collaborative) or knowledge-based algorithms. In this paper, we present a hybrid syste...