About Aaushi eReference

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Meaning of Aaushi: One who is careful, knowledgeable and blessed with a long life.

Aaushi is a California non-profit organization* delivering a free, web-based, intelligent medical reference for inpatient and outpatient diagnosis and management of patients in internal medicine and geriatrics. The reference is organized to provide rapid access to specific information at the point of patient care. It is a tool that works in the clinic, at the bedside, or in ABIM's Longitudinal Knowledge Assessment (LKA) board examinations.

  • Aaushi is classified by the Department of the Treasury Internal Revenue Service IRC Section 501(c)(3) as a public charity. Donations to Aaushi are tax deductable under IRC Section 170.

Mission statement:

Aaushi's mission is to deliver a web-based biomedical electronic resource both for the purpose of increasing efficiency of medical practice through clinical decision support, as well as providing a knowledge system of basic biomedical science. The information content is tailored to students, practicing medical personnel, and biomedical science educators and researchers. Aaushi aims to promote new ideas and enhance research into improving patient outcomes in diseases of aging such as cancers, cardiovascular diseases and neurodegenerative diseases. Ultimately, the goals are to enhance our understanding of human aging and to improve the lives of older patients. Aaushi is continually expanding with the goal to be a unique, extensive, and comprehensive scientific medical reference tool available to anyone.


Contact: AaushiNonprofit@gmail.com


About the authors:

1. Sheldon S Ball, Ph.D, M.D.

Education:
M.D., University of Miami, 1983
Ph.D., University of California at Davis, 1978, Chemistry
B.S., University of California at Davis, 1974
Certification:
Board Certification in Clinical Pathology, 1989
Board Certification in Internal Medicine, 1999-2029
Board Certification in Geriatrics, 2002-2023

2. Vei H Mah, MD

Education:
M.D., Oregon Health & Science University, 1983
B.S., Oregon State University, 1977
Certification:
Board Certification in Pathology, 1989
Board Certification in Neuropathology, 1989

Aaushi is a product of Senex, a programming project began in 1988 designed for knowledge representation in the domain of molecular pathology, especially diseases of old age. Senex is written in Common Lisp, a programming language created by John McCarthy introduced in 1960 used for exploratory programming. Over the next decade, it became apparent that the success of medical knowledge was ultimately driven by the delivery of patient care and that there was an opportunity within informatics to translate developments in molecular pathology to delivery of patient care at the point of patient contact. Below, we take you through the story of the evolution of Senex. In the final paragraphs, we describe the rationale for creation of Aaushi, this MediaWiki interface and the strategy for continuing to build Aaushi as we move forward.


Evolution of Senex:

Senex began as a functional prototype addressing:

 1) representation of medical & biological information
 2) presentation of data  
 3) reasoning with this information*
  • To facilitate reasoning with information, information within Senex has been expressed in both a machine-readable & human-readable format.

Senex development began as a project in knowledge representation. In particular, how can the following questions be addressed in the form of computer representations?

 - What are the essential features of elements that give rise to the formation of molecules & ions?
 - What are the essential features of biomolecules that give rise to their function within cellular compartments & individual cells? 
 - What are the essential features of intra- & intermolecular interactions that participate in molecular pathways & cascades?
 - What are the features of pathways & cascades that facilitate cellular metabolism, cell division, & cell death?
 - What are the features of cells that give rise to their interactions with other cells, within tissues, organs & organ systems?
 - What are the features of diseases that are essential to understand for the practice of medicine & how are those features related to changes in organ system, organ, tissue, cellular, compartmental & molecular function?

The questions addressed in knowledge representation must also accept that uncertainty will always be associated with scientific data. The uncertainty may be quantitative or qualitative in nature. Qualitative uncertainty shares representational issues with generalizations [2], the distinction being especially important when reasoning with information.

The object-oriented paradigm of the Common Lisp Object System (CLOS) [6] provides a means of generating structures of arbitrary complexity and also a means of organizing information within a classification structure. The CLOS classification* within Senex serves several functions, including:

 - structure for representation of biological information, 
 - inheritance of properties common to similarly classified objects, 
 - customized operations through methods defined on specific classes, 
 - representation of qualitative uncertainty & generalization, 
 - entry points for specification of queries. 

Along with the classification structure of Senex (type-of relationships) there is a component-of hierarchy for use with anatomy & histology.

Extensive use of object-oriented techniques has been employed in the development of Senex [1,2,3,5]. These include object-oriented classification features and the metaobject protocol [4]. The metaobject protocol provides a framework for the system to examine its own behavior (introspection) & modify it to achieve a desired effect.


Creation of Aaushi:

In parallel with the development of representation in molecular pathology, Senex provides a clinical component to integrate with molecular features of disease. This has been implemented as a point of patient contact medical reference for internal medicine and geriatrics, delivered as a MediaWiki web application Aaushi (https://aaushi.info). The goal has been to provide a familiar easy to use interface that allows rapidly focusing in on specific medical information needed in the clinic and at the bedside. A second website https://aaushi.org contains a functional lisp engine, facilitating real time computations such as differential diagnosis and various calculators. Both web applications have links to the underlying molecular pathology.

The American Board of Internal Medicine (ABIM) has launched a Longitudinal Knowledge Assessment (LKA) that allows physicians to complete Geriatric Board requirements at home or at work using references that they would use during the course of performing their job as a physician. Aaushi (http://Aaushi.info) is useful for answering these questions within the allotted time of four minutes. I used Aaushi to answer the first 7 sets of questions of the ABIM Geriatrics LKA.

I have also used Aaushi to answer all questions in MKSAP 11-19, the Geriatric Review Syllabus GRS (8-11), and NEJM Knowledge+ Cardiology, Pulmonary, Infectious Disease, Oncology, Neurology, Rheumatology, Pain Management and Geriatrics. Aaushi contains no questions or reference to examination questions, only information organized to allow one to find answers to these questions and others quickly.

I also use Aaushi in my part time work as an internist and geriatrician. I run Aaushi under Google Chrome on a Windows platform running the clinic's EMR. I can look up guidelines to specific details quickly at the point of patient care for diseases, drugs, labs, radiology & other procedures. Aaushi is updated weekly as part of an effort to keep Aaushi current. The information in Aaushi has been and is currently collected, integrated and modified by reading literature and manually entering the information. There is no ChatGPT-like system used in the process.

The organization of Aaushi facilitates finding answers to specific questions under stress of time constraints. The concise (bulleted) format of information in connection with navigational tools allows for the rapid focus & retrieval of specific information. The hierarchical organization of concepts in conjunction with a mapping of synonyms and the implementation of word completion provides a first level of focus. The inclusion of different search pathways to sharpen focus on specific information provides flexibility to Aaushi searches. For example, one might approach specific information from a perspective of disease, sign/symptom, syndrome, organism/pathogen, pharmacology, anatomy, radiology, laboratory test or other clinical procedure. A second layer of focus is provided by the content box that identifies and provides a direct link to each subheading of a given concept. For example, if the question is about management, select management from the Contents box and so forth. A third level of focus is the concise bulleted format of Aaushi organized in a logical strategy with no rambling prose to sift through. A fourth level of focus is the extensive highlights, all algorithmically implemented during the build process. Aaushi is extensively referenced.


Aaushi is a free reference intended for use by health care professionals*. Feedback is appreciated.

  • Aaushi does not provide advice for diagnosis or management of individual patients. This is the responsibility of the patient's health care provider.

References:

1) Steele GL.

  Common LISP the Language. 2nd ed. Digital Press 1990

2) Ball SS, Mah VH.

  Senex: CLOS in molecular pathology. 
  Uncertainty, generalization, and the comparison of objects.
  In: Proceedings of the 4th Annual Lisp Users and Vendors 
  Conference; 1994 August 15-19; Berkeley, CA.

3) Keene SE.

  Object Oriented Programming in Common LISP, Addison-Wesley, Reading MA, 1989. 

4) Kiczales G.

  The Art of the Metaobject Protocol, MIT Press, Cambridge MA,1991.

5) Gu H, et al.

  Representing the UMLS as an object-oriented database: modeling issues and advantages. 
  Journal of the American Medical Informatics Association 2000;(7):66-80.

6) Lindvall JM, Blomberg KE, Smith CI.

  In silico tools for signal transduction research. 
  Brief Bioinform 4(4):315-24, 2003