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Dynamic arrays for fast, efficient, data manipulation during image analysis: a new software tool for exploratory data analysis.

Memory reallocation is used to construct a run-time data structure for fast/efficient storage of information during collection and analysis. The data structure presented uses dynamic memory but does not require the use of pointers to link nodes of information together. It allows for simple and efficient access to data via array indexing rather than through the use of lists or tree structures and it provides flexibility for competing storage requirements that are determined dynamically. The data structure is developed in the C programming language and a suite of ANSI standard C subroutines that make up a run-time data structure management system is provided.

Abstracting and Indexing

A framework for uniform access to data, software and knowledge.

An object-oriented framework is presented that offers integration of various types of entities at one workstation. Five types of entities are distinguished: data, knowledge, functions, presentation forms and hardware, and for each of these entities an 'accessor' is introduced. An accessor offers abstraction from the particularities of access to the entities. For the interaction with this framework a programming language has been defined. A restricted form of the framework has been used to implement a prototype medical workstation for the support of clinical data analysis.

Artificial Intelligence

An intelligent end-effector for a rehabilitation robot.

A UMI RTX robot, modified with limited end-effector sensors and a restricted but effective vision system, is currently used in a developmental education setting for severely physically disabled children. The low physical and cognitive abilities of the children involved in the project require a semi-autonomous robot with environmental sensing capability to operate in a task oriented mode. A variety of low-cost sensors including proximity, distance, force and slip sensors, have been investigated for integration in end-effectors for the RTX robot. The sensors employed on a modified end-effector are detailed and experimental results are presented. A design for an end-effector with integrated sensors is discussed. The integration of the sensor information into a high-level, task-oriented programming language is detailed and examples of high-level control sequences using sensor inputs are presented. Finally, the development of intelligent gripping strategies based on sensor information is discussed.

Artificial Intelligence

A software-controlled EKG simulator.

This design allows generation of a wide range of waveforms from subaudio to ultrasonic directly via software. Waveforms may be calculated on the fly by suitable algorithms or produced from previously created lookup tables. The heart of the design is a fast 16-bit processor which directly executes the Forth programming language. A simple R/2R digital-to-analog converter is coupled to a parallel output port to produce the desired waveforms. This device has been used to generate realistic-appearing normal and abnormal EKG tracings in the lab.

Algorithms

Programming medical rosters in Prolog.

The Logic Programming language, Prolog, is used to schedule the medical duty roster for a French psychiatric hospital. Each of the seventeen doctors participating is asked to fill in a form indicating his preferences (prefers, can or cannot) for the slots (days and weekends) of a roster covering a period of three months. An algorithm has been designed which seems to produce an optimal solution, in the sense that as many participants as possible are satisfied. First of all, the program fills in the 'preferred' slots, then the 'possible' slots and finally the 'not-impossible' slots. A number of constraints are applied: two consecutive roster slots are not allowed and the number of allocations is limited for each person. If more than one person is a candidate for a given slot at a given preference level, then a probabilistic conflict resolution procedure is put into action. Prolog, which is modular and easily modifiable, seems, with its declarative interpretation and backtracking mechanism, to be well adapted to the solution of such problems.

Algorithms

Development of a computer-aided reference system for differential diagnostics support.

In a situation of uncertain diagnosis, physicians may spend valuable time consulting relevant literature, often with unsatisfactory results. Therefore, our aim was to develop a computer system which supports differential diagnostics via rapid and comprehensive searches through information in literature. Based on entered signs and symptoms our prototype is able to offer probable diagnoses. Subsequently, further examinations and tests are suggested to confirm or exclude a certain disease. Thus, the final diagnosis is made gradually by differentiation of possible diseases. Our first attempt consisted in representing knowledge in a rule-based PROLOG system. However, because nearly all information for a sign-oriented differential diagnosis can be represented with very few relations only, we turned to a fact-oriented representation of signs and diseases. Access was possible via PROLOG or an imperative programming language. The index-sequential access on a fact-oriented representation of knowledge was suitable to manage a large knowledge base, which is necessary for a thorough differential diagnosis. A pointer structure was recently examined in order to handle different object-to-object relations. Efficient information processing is now possible which provides short response times using even broad knowledge bases.

Diagnosis, Computer-Assisted

An object oriented approach to interpret medical knowledge based on the Arden syntax.

A method is presented where medical knowledge modules, written in the Arden Syntax, are used in a decision-support system (DSS). Knowledge modules are, after syntax-checking, translated into the object oriented programming language C++, compiled and linked to the DSS. The object oriented approach together with developed tools, such as knowledge editor and translator, makes it possible to implement the Arden Syntax and to get an efficient, easy-maintained DSS. Work on a prototype shows that this approach has several advantages when building a DSS where medical knowledge is represented in the Arden Syntax.

Artificial Intelligence

A parallel implementation of the backward error propagation neural network training algorithm: experiments in event identification.

An artificial neural-network-based (ANN) event detection and alarm generation system has been developed to aid clinicians in the identification of critical events commonly occurring in the anesthesia breathing circuit. To detect breathing circuit problems, the system monitored CO2 gas concentration, gas flow, and airway pressure. Various parameters were extracted from each of these input waveforms and fed into an artificial neural network. To develop truly robust ANNs, investigators are required to train their networks on large training data sets, requiring enormous computing power. We implemented a parallel version of the backward error propagation neural network training algorithm in the widely portable parallel programming language C-Linda. A maximum speedup of 4.06 was obtained with six processors. This speedup represents a reduction in total run-time from 6.4 to 1.5 h. By reducing the total run time of the computation through parallelism, we were able to optimize many of the neural network's initial parameters. We conclude that use of the master-worker model of parallel computation is an excellent method for speeding up the backward error propagation neural network training algorithm.

Algorithms

monarchr: an R package for querying biomedical knowledge graphs.

SUMMARY: Biomedical knowledge graphs (KGs) aggregate and provide a wealth of information, linking genes and their variants, diseases, phenotypes, and much more. While these data are available in raw and API-hosted form, to date, functionality for working with KGs in the R programming language has been limited. We introduce monarchr, a package for querying and manipulating KG data. Support for the expansive Monarch Initiative KG is built in, and monarchr can accommodate any KG in the Knowledge Graph eXchange (KGX) format. This tidy-inspired interface offers researchers an intuitive, iterative approach to querying and visualizing KG data. AVAILABILITY AND IMPLEMENTATION: Source code, documentation, and installation instructions are available at https://github.com/monarch-initiative/monarchr.

Software

Setting up a decision support system with decision tables.

The aim of our study was to develop a decision support system using a conventional method which can be used as a shell for different applications. So it was necessary to find a method which allows separation of decision principles and decision algorithms. In addition, documentation of the patient records should be simplified. This could be attained by using the decision table technique and the programming language MUMPS. The general system developed was applied to the therapy decision for patients with liver metastases. The application system was clinically evaluated in a randomized group of patients. In 84% of the study group the therapy proposal of the system concurred with the therapy actually applied. Representation of knowledge in the form of tables is easily understandable by physicians. Since decision tables can be seen as a medium of communication between physician and system manager, knowledge acquisition is simplified.

Algorithms

ShortCake: an integrated platform for efficient and reproducible single-cell analysis.

SUMMARY: Recent advances in single-cell analysis have introduced new computational challenges. Researchers often need to use multiple analysis tools written in different programming languages while managing version conflicts between related packages within a single workflow. For the research community, minimizing the time spent on environment setup and installation issues is essential. We present ShortCake, a containerized platform that integrates a suite of single-cell analysis tools written in R and Python. ShortCake isolates competing Python tools into separate virtual environments that can be easily accessed within a Jupyter notebook. This enables users to effortlessly transition between various environments, including R, even within a single notebook. Additionally, ShortCake offers multiple "flavors," enabling users to select container images tailored to their specific needs. ShortCake provides a unified environment with fixed versions of various tools, thus streamlining workflows, reducing setup time, and improving reproducibility. AVAILABILITY AND IMPLEMENTATION: The ShortCake image is available on DockerHub (https://hub.docker.com/r/rnakato/shortcake) and Zenodo (DOIs: 10.5281/zenodo.17116765 and 10.5281/zenodo.17118158). The source code is available on GitHub (https://github.com/rnakato/ShortCake).

Single-Cell Analysis

A parallel computing approach to genetic sequence comparison: the master-worker paradigm with interworker communication.

We have implemented a parallel version of a dynamic programming biological sequence comparison algorithm to study the potential applicability of using parallel computers for genetic sequence comparisons. Our parallel program is built using C-Linda, a machine-independent parallel programming language, and was tested on both a 10 CPU Sequent Symmetry and a 64 CPU Intel Hypercube. C-Linda implements a shared associative memory model, "tuple space," through which multiple processes can communicate and coordinate control. In our master-worker (MW) parallel implementation, a master process creates several worker processes, extracts a test sequence and multiple library sequences from a database and stores them in tuple space. Each worker reads the test sequence and then repeatedly extracts library strings from tuple space, performs pairwise sequence comparison using a local comparison algorithm to generate a similarity score, and returns the similarity scores to tuple space. The master collects the scores from tuple space and identifies the best match over all library sequences. We also implemented a method of global interworker communication to reduce the total search time by stopping those string comparisons that had no chance of improving on the current best match. Comparisons of the total run time, speedup, and efficiency were made for parallel and sequential versions of a basic MW implementation as well as versions with the global abort threshold.

Algorithms

Two programs for predicting adult stature for individuals.

Two computer programs are described which use the new RWT method to predict adult stature for individuals. This method, developed and described by Roche et al. is the best and most accurate one available to date. The two programs are prepared with different aims in different languages. Program 1 is interactive, written in BASIC and is aimed for the clinician who needs predictions for just a few individuals at a time. Program 2 is written in FORTRAN and is meant for large-scale batch processing. It is thought that this mode is better for the researcher who is more interested in large-scale testing of hypotheses about such things as the efficacy of intervention programs in human growth.

Adult

A comprehensive cardiovascular waveform analysis program for IBM-compatible personal computers.

Computerized cardiovascular waveform processing has become a necessary and fundamental tool in the analysis of physiologic data. The availability of numerous commercial data-analysis programs has significantly enhanced the efficiency of waveform analysis. Many such programs come with their own programming language, which enables the researcher to create an application program suited to a specific series of calculations. Once written, an application program can significantly increase the efficiency with which data from a specific experiment can be analyzed. However, creating or modifying a program for each new experimental protocol can be time-consuming, especially in the error-detection and verification stages. Single-purpose programs also prove somewhat inflexible to unexpected changes in experimental formats. These problems suggested the need for a more flexible program, but one that is nevertheless specifically suited to the analysis of cardiovascular signals. This need led to the development of a program designed in collaboration with surgeons and physiologists. This program addresses some important analysis problems in cardiovascular research, and allows the user to survey and manipulate cardiovascular waveforms in an intuitive and spontaneous manner.

Algorithms

[The physician and the computer. 22. Programming in the Prolog language].

A modern tool of interaction with the computer is the programming language Prolog. The authors discuss its position among other languages, emphasize its different character (declarative programming). They outline basic structures of Prolog and its type of function. They also give examples of creating data bases of patients and the possibility to use this language in the creation of expert systems in medicine.

Medical Informatics

Biological assays for irritant, tumor-initiating and -promoting activities. III. Computer-assisted management and validation of biodata generated by standardized initiation/promotion protocols in skin of mice.

The initiation/promotion standard protocol 28 (protocol 28), developed and used previously as an experimental model to verify the cancerogenic process of initiation/promotion in mouse skin, was revised in three aspects: (a) statistically it was shown sufficient to use, per promoter dose group, 16 colony-outbred female NMRI mice: (b) by weekly individual records of tumor response (and health status) of each mouse in a dose group, cumulative tumor incidences (and mean and extreme body weights) are determined; from these data the collective records (tumor response, health status), the only data accessible from protocol 28, may be generated in addition; (c) the details of dose groups and all data on tumor response and health status are processed by computer using the program package PAPILLOM. The latter was developed specifically for this purpose, is written in the programming language APL and designed for easy handling by staff of animal laboratories. The program package calculates, from the individual records per promoter dose group, cumulative tumor incidences (and survival data) with confidence limits for any one exposure time, and the package may be linked to programs for statistical validations. In addition, from the collective records it calculates the tumor rates, tumor yields and survival rates for any one exposure time. These data, obtained by either of the standard protocols (16 or 28), are fully comparable. For pure compounds they may be used to calculate semiquantitative tumor-promoting potencies. These values for more than 80 polyfunctional diterpenes of the tigliane, ingenane and daphnane type, scattered in or calculated from previous papers, together with their irritancies, were compiled. Within recent years, computer-assisted standard protocol 16 has been used to handle and evaluate about 1000 promoter dose groups. Protocol 16 allows one to extract and utilize more and better toxicological information on tumor response and health status from any one dose group, utilizing significantly fewer experimental animals than required by protocol 28. Thus, the computer-assisted standard protocol 16 optimizes the utility of the experimental model of mouse skin for the amount, quality and management of experimental data as well as for the requirements of animal protection.

Animals

Programmed instruction.

This report presents a description of the principles of programmed instruction and an explanation of all major components of a program. No attempt is made to review or critique all available speech and language programs, but certain programs are discussed in some detail in order to illustrate adequate application of programming principles.

Behavior Therapy

The facilitative effects of incidental teaching on preposition use by autistic children.

In a comparison of incidental teaching and traditional training procedures, three language-delayed autistic children were taught expressive use of prepositions to describe the location of preferred edibles and toys. Traditional highly structured training and incidental teaching procedures were used in a classroom setting, and generalization was assessed during free-play sessions. Results clearly indicate that incidental teaching promoted greater generalization and more spontaneous use of prepositions. These findings have important implications for language programming and teacher training, suggesting that incidental teaching should be included as a standard component of language development curricula for autistic and other developmentally delayed children.

Autistic Disorder