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Home / Proceedings / Papers from the 1999 AAAI Spring Symposium /

Predictive Toxicology of Chemicals: Experiences and Impact of AI Tools

Contents

  • COMET: The Approach Of A Project In Evaluating Toxicity

    E. Benfenati, S. Pelagatti, P. Grasso, G. Gini

    PDF
  • Structure-Cytotoxicity/Antiviral Activity Relationship Studies of Nucleoside Analogs Using Structure-Activity Maps

    Ravi R. Parakulam, Mathew L. Lesniewski, Michael A. Marquis II, and Chun-che Tsai

    PDF
  • Discovery of Knowledge about Drug Side Effects in Clinical Databases based on Rough Set Model

    Shosaku Tsumoto

    PDF
  • Utilization of Predictive Toxicology Software and Similar Tools For Health Risk Assessment of Chemicals and Polymers

    Ranjan Bose

    PDF
  • Artificial Neural Networks As Statistical Tools In SAR/QSAR Modeling

    H. G. Claycamp, N. B. Sussman, O. Macina, H. S. Rosenkranz

    PDF
  • Finding Frequent Substructures In Chemical Compounds

    Luc Dehaspe, Hannu Toivonen, and Ross Donald King

    PDF
  • Long Term Development of Toxicology Databases: The Experience Gathered By The Joint Research Centre Of The European Commission Within The ECDIN And IUCLID Projects

    Flavio Argentesi and Annabelle Ascher

    PDF
  • Predicting Chemical Carcinogenesis in Rodents with Artificial Neural Networks and Symbolic Rules Extracted from Trained Networks

    Brian A. Stone, Dennis Bahler

    PDF
  • Discovering Substructures in the Chemical Toxicity Domain

    Ravindra N. Chittimoori, Lawrence B. Holder, and Diane J. Cook

    PDF
  • Predicting Rodent Carcinogenicity in a Set of 30 Test Agents Using Discriminant Analysis and Bayesian Classifiers

    Carol A. Wellington

    PDF
  • Data Quality Issues In Toxicological Knowledge Discovery

    Christoph Helma, Eva Gottmann, Stefan Kramer, and Bernhard Pfahringer

    PDF
  • Similarity, Diversity, and the Comparison of Molecular Structures

    Guido Sello

    PDF
  • Some Results for the Prediction Of Carcinogenicity Using Hybrid Systems

    Giuseppina Gini, Marco Lorenzini, Angela Vittore, Emilio Benfenati, and Paola Grasso

    PDF
  • The Utility of Multiple Random Sampling in the Development of SAR Models

    N. B. Sussman, O. T. Macina, H. G. Claycamp, S. G. Grant, H. S. Rosenkranz

    PDF
  • Use of Statistical And Neural Net Methods In Predicting Toxicity Of Chemicals: A Hierarchical QSAR Approach

    Subhash C. Basak, David W. Opitz, Krishnan Balasubramanian, Brian D. Gute, Gregory D. Grunwald

    PDF
  • Prediction of Chemical Carcinogenicity in Rodents by Machine Learning of Decision Trees and Rule Sets

    Dennis Bahler and Douglas W. Bristol

    PDF
  • QSPR and QSAR Models Derived with CODESSA Multipurpose Statistical Analysis Software

    Mati Karelson, Uko Maran, Yilin Wang, and Alan R. Katritzky

    PDF
  • Adaptive Structure Processing with ANN: Is It Useful For Chemical Applications?

    Christoph Goller

    PDF
  • Computational Intelligence and Predictive Toxicology

    Adolf Grauel, L. A. Ludwig, I. Renners, F. Berk

    PDF
  • A Comprehensive Approach to Argumentation

    Philip N. Judson and Jonathan Vessey

    PDF
  • Overview of Different Artificial Intelligence Approaches Combined with a Deductive Logic-based Expert System for Predicting Chemical Toxicity

    Ferenc Darvas, Atkos PappI, Alex Allerdyce, Emilio Benfenati, Giuseppina Gini, Milofi Tichy, Nicholas Sobb, and Aida Citti

    PDF
  • A Distributed Solution to the PTE Problem

    Ignacio Giráldez, Charles Elkan, Daniel Borrajo

    PDF
  • A Hybrid Approach To Risk Assessment For Multiple Pathway Chemical Exposures

    T. Rajkumar

    PDF
  • A Graphical Technique for Preliminary Assessment of Effects on DNA Sequences from Toxic Substances

    A. Nandy, C. Raychaudhury, S. C. Basak

    PDF
  • Membrane-Interaction QSAR Analysis: Application To The Estimation of Eye Irritation of Organic Compounds

    Amit S. Kulkarni, A. J. Hopfinger, and Jose S. Duca

    PDF
  • Argumentation and Risk Assessment

    Simon Parsons, John Fox, and Andrew Coulson

    PDF
  • Rule Generation by Means of Lattice Theory

    R. Brüggemann S. Pudenz, H-G. Bartel

    PDF
  • Predictive Toxicology and Mixtures of Chemicals

    Milofi Tichy, Vaclav Borek Dohalsky, Marian Rucki, Ladislav Felt

    PDF
  • Combining Recursive Partitioning and Uncertain Reasoning for Data Exploration and Characteristic Prediction

    Kristen L. Mello and Steven D. Brown

    PDF
  • The Requirements For Registration Of Plant Protection Products In The EU

    P. Ciocca, P. Grasso

    PDF
  • Multiple Formula Approach for Structure-Cytotoxicity/Antiviral Activity Relationship Studies of Nucleoside Analogs

    Mathew L. Lesniewski, Ravi R. Parakulam, Merideth R. Marquis, and Chun-che Tsai

    PDF
  • Development of Knowledge Rules for Cancer Expert System for Prediction of Carcinogenic Potential of Chemicals: USEPA Approach

    Yin-tak Woo, David Y. Lai, Joseph C. Arcos, and Mary F. Argus

    PDF
  • A QSAR – Bayesian Neural Network Model To Identify Molecular Properties Causing Eye Irritation In Cationic Surfactants

    Grace Y. Patlewicz, Wael El-Deredy

    PDF
  • On Characterization of Pharmacophore

    Milan Randic

    PDF
  • Using Inductive Logic Programming to Construct Structure-Activity Relationships

    Ashwin Srinivasan and Ross D. King

    PDF
  • Representational/Efficiency Issues In Toxicological Knowledge Discovery

    Bernhard Pfahringer, Eva Gottmann, Stefan Kramer, Christoph Helma

    PDF

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