Supported Text Analytics for health entity categories
Text Analytics for health processes and extracts insights from unstructured medical data. The service detects and surfaces medical concepts, assigns assertions to concepts, infers semantic relations between concepts and links them to common medical ontologies.
Text Analytics for health detects medical concepts in the following categories.
Anatomy
Entities
BODY_STRUCTURE - Body systems, anatomic locations or regions, and body sites. For example, arm, knee, abdomen, nose, liver, head, respiratory system, lymphocytes.
Demographics
Entities
AGE - All age terms and phrases, including ones for patients, family members, and others. For example, 40-year-old, 51 yo, 3 months old, adult, infant, elderly, young, minor, middle-aged.
GENDER - Terms that disclose the gender of the subject. For example, male, female, woman, gentleman, lady.
Examinations
Entities
EXAMINATION_NAME – Diagnostic procedures and tests, including vital signs and body measurements. For example, MRI, ECG, HIV test, hemoglobin, platelets count, scale systems such as Bristol stool scale.
External Influence
Entities
ALLERGEN – an antigen triggering an allergic reaction. For example, cats, peanuts.
General attributes
Entities
COURSE - Description of a change in another entity over time, such as condition progression (e.g., improvement, worsening, resolution, remission), a course of treatment or medication (e.g., increase in medication dosage).
DATE - Full date relating to a medical condition, examination, treatment, medication, or administrative event.
DIRECTION – Directional terms that may relate to a body structure, medical condition, examination, or treatment, such as: left, lateral, upper, posterior.
FREQUENCY - Describes how often a medical condition, examination, treatment, or medication occurred, occurs, or should occur.
TIME - Temporal terms relating to the beginning and/or length (duration) of a medical condition, examination, treatment, medication, or administrative event.
MEASUREMENT_UNIT – The unit of measurement related to an examination or a medical condition measurement.
MEASUREMENT_VALUE – The value related to an examination or a medical condition measurement.
RELATIONAL_OPERATOR - Phrases that express the quantitative relation between an entity and some additional information.
Genomics
Entities
VARIANT - All mentions of gene variations and mutations. For example, c.524C>T, (MTRR):r.1462_1557del96
GENE_OR_PROTEIN – All mentions of names and symbols of human genes as well as chromosomes and parts of chromosomes and proteins. For example, MTRR, F2.
MUTATION_TYPE - Description of the mutation, including its type, effect, and location. For example, trisomy, germline mutation, loss of function.
EXPRESSION - Gene expression level. For example, positive for-, negative for-, overexpressed, detected in high/low levels, elevated.
Healthcare
Entities
ADMINISTRATIVE_EVENT – Events that relate to the healthcare system but of an administrative/semi-administrative nature. For example, registration, admission, trial, study entry, transfer, discharge, hospitalization, hospital stay.
CARE_ENVIRONMENT – An environment or location where patients are given care. For example, emergency room, physician’s office, cardio unit, hospice, hospital.
HEALTHCARE_PROFESSION – A healthcare practitioner licensed or non-licensed. For example, dentist, pathologist, neurologist, radiologist, pharmacist, nutritionist, physical therapist, chiropractor.
Medical condition
Entities
DIAGNOSIS – Disease, syndrome, poisoning. For example, breast cancer, Alzheimer’s, HTN, CHF, spinal cord injury.
SYMPTOM_OR_SIGN – Subjective or objective evidence of disease or other diagnoses. For example, chest pain, headache, dizziness, rash, SOB, abdomen was soft, good bowel sounds, well nourished.
CONDITION_QUALIFIER - Qualitative terms that are used to describe a medical condition. All the following subcategories are considered qualifiers:
- Time-related expressions: those are terms that describe the time dimension qualitatively, such as sudden, acute, chronic, longstanding.
- Quality expressions: Those are terms that describe the “nature” of the medical condition, such as burning, sharp.
- Severity expressions: severe, mild, a bit, uncontrolled.
- Extensivity expressions: local, focal, diffuse.
CONDITION_SCALE – Qualitative terms that characterize the condition by a scale, which is a finite ordered list of values.
Medication
Entities
MEDICATION_CLASS – A set of medications that have a similar mechanism of action, a related mode of action, a similar chemical structure, and/or are used to treat the same disease. For example, ACE inhibitor, opioid, antibiotics, pain relievers.
MEDICATION_NAME – Medication mentions, including copyrighted brand names, and non-brand names. For example, Ibuprofen.
DOSAGE - Amount of medication ordered. For example, Infuse Sodium Chloride solution 1000 mL.
MEDICATION_FORM - The form of the medication. For example, solution, pill, capsule, tablet, patch, gel, paste, foam, spray, drops, cream, syrup.
MEDICATION_ROUTE - The administration method of medication. For example, oral, topical, inhaled.
Social
Entities
FAMILY_RELATION – Mentions of family relatives of the subject. For example, father, daughter, siblings, parents.
Treatment
Entities
TREATMENT_NAME – Therapeutic procedures. For example, knee replacement surgery, bone marrow transplant, TAVI, diet.
Supported Assertions
Assertion modifiers are divided into three categories, each one focuses on a different aspect. Each category contains a set of mutually exclusive values. Only one value per category is assigned to each entity. The most common value for each category is the Default value. The service’s output response contains only assertion modifiers that are different from the default value.
Certainty
provides information regarding the presence (present vs. absent) of the concept and how certain the text is regarding its presence (definite vs. possible).
Positive (Default): the concept exists or happened.
Negative: the concept does not exist now or never happened.
Positive_Possible: the concept likely exists but there is some uncertainty.
Negative_Possible: the concept’s existence is unlikely but there is some uncertainty.
Neutral_Possible: the concept may or may not exist without a tendency to either side.
Conditionality
provides information regarding whether the existence of a concept depends on certain conditions.
None (Default): the concept is a fact and not hypothetical and does not depend on certain conditions.
Hypothetical: the concept may develop or occur in the future.
Conditional: the concept exists or occurs only under certain conditions.
Association
describes whether the concept is associated with the subject of the text or someone else.
Subject (Default): the concept is associated with the subject of the text, usually the patient.
Someone_Else: the concept is associated with someone who is not the subject of the text.
Next steps
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