David Heckerman

An approximate nonmyopic computation for value of information

It is argued that decision analysts and expert-system designers have avoided the intractability of exact computation of the value of information by relying on a myopic assumption that only one additional test will be performed, even when there is an opportunity to make large number of observations. An alternative to the myopic analysis is presented. In particular, an approximate method for computing the value of information of a set of tests, which exploits the statistical properties of large samples, is given. The approximation is linear in the number of tests, in contrast with the exact computation, which is exponential in the number of tests. The approach is not as general as in a complete nonmyopic analysis, in which all possible sequences of observations are considered. In addition, the approximation is limited to specific classes of dependencies among evidence and to binary hypothesis and decision variables. Nonetheless, as demonstrated with a simple application, the approach can offer an improvement over the myopic analysis. >

Advances in probabilistic reasoning

This paper discuses multiple Bayesian networks representation paradigms for encoding asymmetric independence assertions. We offer three contributions: (1) an inference mechanism that makes explicit use of asymmetric independence to speed up computations, (2) a simplified definition of similarity networks and extensions of their theory, and (3) a generalized representation scheme that encodes more types of asymmetric independence assertions than do similarity networks.

An evaluation of the diagnostic accuracy of Pathfinder

We present an evaluation of the diagnostic accuracy of Pathfinder, an expert system that assists pathologists with the diagnosis of lymph node diseases. We evaluate two versions of the system using both informal and decision-theoretic metrics of performance. In one version of Pathfinder, we assume incorrectly that all observations are conditionally independent. In the other version, we use a belief network to represent accurately the probabilistic dependencies among the observations. In both versions, we make the assumption--reasonable for this domain--that diseases are mutually exclusive and exhaustive. The results of the study show that (1) it is cost effective to represent probabilistic dependencies among observations in the lymph node domain, and (2) the diagnostic accuracy of the more complex version of Pathfinder is at least as good as that of the Pathfinder expert. In addition, the study illustrates how informal and decision-theoretic metrics for performance complement one another.

Surface tension sound in superfluid helium films adsorbed on alumina powder

Sound propagation has been studied in He II films adsorbed on alumina powder grains (Al2O3). Sound velocity and adsorption isotherm data provide evidence that surf ace tension forces can exceed the van der Waals forces as the film thickness increases. A model of capillary condensation at the points where the powder grains touch accounts for many of the qualitative features of the data. The surface tension sound velocity decreases with increasing powder grain size.

Surface tension restoring forces on gravity waves in narrow channels

Surface tension restoring forces are investigated for low amplitude gravity waves propagating in narrow channels. Liquids which do not wet the container walls experience a nonuniform displacement of the meniscus as the wave passes. The variation of surface curvature leads to a surface tension force which increases the velocity of the gravity wave. The effect is substantial in experiments with water in Plexiglass channels. The dependence on channel width and contact angle has been investigated, and agreement is found with a simple theoretical model. Addition of a wetting agent to the water eliminates the effect, decreasing the velocity to within 1% of the classical dispersion relation.

Pressure Release Superleak Sound Modes in He II

The sound modes of He II in a waveguide partially packed with superleak are investigated for the case of a free surface within the waveguide. In the limit of zero vapor density, two propagating modes are found: one a gravity wave whose velocity depends on the superfluid fraction, and the other a temperature wave which is analogous to adiabatic U-tube osculations. With finite vapor the U-tube mode in pure 4He mixes strongly with the vapor sound; however, in 3He-4He mixtures it is uncoupled from the vapor and is observable. Experimental results are in qualitative agreement with the theory.

Expert systems and videodisc in surgical pathology

We have developed an integrated educational tool consisting of an expert system connected to a videodisc for the field of lymph node pathology. The expert system makes diagnosis on 65 diseases of lymph nodes based on histopathologic, clinical and immunologic features. The system recommends to the user additional histologic features that should be evaluated to narrow the differential diagnosis. Moreover, the system explains its recommendations. The system also provides instant access to criteria of diseases, definitions of histologic features, the value of immunology and molecular biologic studies, and journal references. The computer controls an analog interactive videodisc containing 6700 slides on lymph node pathology. The slides are displayed on a separate monitor connected to the videodisc. The slides are organized by diseases, by histologic features, and in a comprehensive lecture format. The system can generate an automatic surgical pathology report, has archival capabilities and ability for creating customized lectures (slide-lecture editing functions). The expert system runs on IBM-XT and IBM compatible MS-DOS personal computers. Expert systems and videodisc for stomach, thymus, breast, skin, are completed and remaining 36 organ systems are under development. The knowledge for each of these systems is being provided by experts in the field. All systems will be completed by 1991.

Identification of essential regulatory elements in the human genome

The identification of essential regulatory elements is central to the understanding of the consequences of genetic variation. Here we use novel genomic data and machine learning techniques to map essential regulatory elements and to guide functional validation. We train an XGBoost model using 38 functional and structural features, including genome essentiality metrics, 3D genome organization and enhancer reporter STARR-seq data to differentiate between pathogenic and control non-coding genetic variants. We validate the accuracy of prediction by using data from tiling-deletion-based and CRISPR interference screens of activity of cis-regulatory elements. In neurodevelopmental disorders, the model (ncER, non-coding Essential Regulation) maps essential genomic segments within deletions and rearranged topologically associated domains linked to human disease. We show that the approach successfully identifies essential regulatory elements in the human genome.