Digital Speech Recognition Systems in an Anatomical Pathology Practice (Online CE Course)

(based on 83 customer ratings)

Authors: Andrey I. Khramtsov, MD, PhD, MS, PA(ASCP)CM and Galina F. Khramtsova, MD, PhD, MS, HTL(ASCP)CM
Reviewer: Dr. Monica Aldulescu, DO, FCAP

This course describes basic principles for using a speech-recognition system in anatomic pathology reporting, including an overview of the equipment. While referencing dictation templates, the course covers principles of the gross description of surgical pathology reports, digital speech-recognition techniques, and refreshes one’s gross pathology knowledge. The current CAP requirements for the gross description (anatomic pathology checklist) will also be reviewed in this course.

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Continuing Education Credits

P.A.C.E.® Contact Hours (acceptable for AMT, ASCP, and state recertification): 1 hour(s)
Approved through 10/31/2026
Approved through 10/31/2026

Objectives

  • Describe the background of speech recognition technology.
  • Define equipment for speech recognition.
  • Describe general principles of gross descriptions and terminology.
  • Define components of gross descriptions.
  • Explain the advantages of speech recognition systems.
  • Describe templates and formatting of surgical pathology reports.
  • Identify College of American Pathologists requirements pertaining to a gross description.

Customer Ratings

(based on 83 customer ratings)

Course Outline

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Additional Information

Level of Instruction: Intermediate
Intended Audience: Histotechnologists, histotechnicians, pathologists' assistants, laboratory supervisors, and laboratory managers. This course is also appropriate for HTL and HT students, cytologists, and pathology residents.
Author Information:
Andrey I. Khramtsov, MD, PhD, MS, PA(ASCP)CM earned an MD/PhD degree at the St. Petersburg State Medical Academy. He was a pathologist in various hospitals and universities in Russia and as a senior scientist at the U. of Chicago. He also holds an MS degree from the Pathologists' Assistant Program at the Rosalind Franklin University of Medicine and Science. Currently, he is working in the Department of Pathology and Laboratory Medicine at Ann & Robert H. Lurie Children's Hospital of Chicago.
Galina F. Khramtsova, MD, PhD, MS, HTL(ASCP)CM earned an MD/PhD degree at the St. Petersburg State I.I. Mechnikov Medical Academy and an MS degree in biology from St. Petersburg State University. She currently works as a senior scientist in the Department of Medicine at the U. of Chicago.
The authors have no conflict of interest to disclose.
Reviewer Information: Monica Aldulescu, DO, FCAP is a board-certified pathologist and dermatopathologist with fellowship training in pediatric pathology. She has a bachelor’s in science in biology from Indiana University in Bloomington, IN and her Doctor of Osteopathic Medicine Degree from Midwestern University Chicago College of Osteopathic Medicine. She completed her Anatomic and Clinical Pathology residency, followed by her Dermatopathology Fellowship at Loyola University Medical Center in Maywood, IL.
Course Description: This course will briefly describe the basic principles for using a speech recognition system in anatomic pathology reporting, including an overview of the equipment. While referencing dictation templates, we will go over principles of the gross description of surgical pathology reports, digital speech recognition techniques, refresh one’s gross pathology knowledge, and subsequently obtain a practical skillset applicable in various facets of the medical practice. In conclusion, we will review the current CAP requirements for the gross description (anatomic pathology checklist). 

General architecture of Digital Speech Recognition Systems


Most common types of dissections of surgical specimens


Shape and texture


The pieces of tissue within the mesh cassette.


The reference planes of the human body in the standard anatomical position.


Lanier VW-110 Standard Cassette Transcriber Dictation Machine


Nuance PN Foot Pedal


Screenshot of manual for pathology trainee in document control of MediaLab.