Logic of medical language

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Logic of medical language

 

 

Medical language is an extended natural language

Language is essential in the medical field, but it can sometimes lead to misunderstandings due to its semantically limited nature and lack of coherence with established scientific paradigms. For instance, terms like "orofacial pain" may have significantly different meanings if interpreted through classical logic rather than formal logic.

The transition from classical to formal logic is not just an additional step, but it requires precise and accurate description. Despite advances in medical technology—such as electromyographs, cone beam computed tomography (CBCT), and digital oral scanning systems—there remains a need for refinement in medical language.

It's crucial to distinguish between natural languages (like English, German, Italian, etc.) and formal languages (like mathematics). Natural languages emerge spontaneously within communities, while formal languages are artificially created for specific applications in fields like logic, mathematics, and computer science. Formal languages have well-defined syntax and semantics, whereas natural languages, despite having grammar, often lack explicit semantics.

To keep the analysis dynamic, an exemplary clinical case will be examined through different language logics:

• Classical language,
• Probabilistic language,
• Fuzzy logic and
• Logic of System.

Clinical case and medical language logic

The patient, Mary Poppins (fictitious name), has been receiving multidisciplinary medical attention for over a decade, involving dentists, general practitioners, neurologists, and dermatologists. Her medical history is summarized as follows:

At 40, Mrs. Poppins noticed small spots of abnormal pigmentation on the right side of her face. Ten years later, after a skin biopsy during dermatology hospitalization, she was diagnosed with localized facial scleroderma (morphea) and prescribed corticosteroids. By age 44, she experienced involuntary contractions of the right masseter and temporal muscles, which increased in frequency and duration over time. At her first neurological evaluation, her face showed significant asymmetry and hypertrophy of the right masseter and temporal muscles. Various diagnoses were made, illustrating the limitations of medical language.

After several investigations—such as anamnesis, stratigraphy, and computed tomography (Figures 1, 2, and 3)—the dentist diagnosed "Temporomandibular Disorders" (TMD). Meanwhile, the neurologist diagnosed "Neuropathic Orofacial Pain" (nOP), minimizing TMD as the primary cause. For objectivity, we refer to her condition as "TMDs/nOP."

We are thus faced with several questions that deserve thorough discussion, as they pertain to clinical diagnostics.

Medical language falls into a hybrid category—it arises from the expansion of everyday language by incorporating technical terminologies such as "neuropathic pain," "Temporomandibular Disorders," or "demyelination." This evolution does not separate it from the inherent ambiguity of natural language, which often lacks precision in critical contexts. For example, the term "disease," crucial in nosology, research, and practice, remains vague in its definition, which can lead to diagnostic uncertainty.

A core question arises: is disease related to the patient as an individual, or does it pertain to the system as a whole (i.e., the organism)? Can a patient who is deemed healthy at a given time $t_{n}$ coexist with a system that was structurally compromised at an earlier point $t_{i,-1}$?

This perspective urges a reconsideration of disease as an evolutionary process rather than a static condition. The dynamic nature of health and disease demands a sophisticated, possibly quantitative, interpretation that factors in temporal variations across biological and pathological systems.

The notion of "language without semantics," treated as irrelevant, highlights a significant issue. Language's inherent semantic interdependence is vital for effective communication.

In short, the debate on whether the patient is ill, or if it is her masticatory system exhibiting pathology, requires a detailed analysis from a medical standpoint. Distinguishing between systemic pathology (masticatory system as a whole) and localized pathology (e.g., TMJ) is key.

Clinical approach

(hover over the images)

• 

  Figure 1: Representation of a patient complaining of "orofacial pain" on the right side of the face.

• 

  Figure 2: Stratigraphy of the patient's TMJ showing condylar flattening and the presence of osteophytes.

• 

  Figure 3: Computed tomography of the TMJ corroborating the stratigraphy findings shown in Figure 2.

Understanding of Medical Terminology

Understanding what "meaning" signifies is a complex topic. The Cambridge Dictionary defines it as "what something expresses or represents." But this definition remains broad and leads to further questions, as different theories offer varied perspectives without a definitive answer.

In linguistic theory, terms act as labels for objects, either concrete or abstract. For example, the word "apple" evokes a clear image of a fruit. But expressions like "orofacial pain" acquire different meanings depending on the context—for a dentist, a neurologist, or for the patient, Mary Poppins, herself.

In the case of Mary Poppins, the neurologist will frame "pain in the right half of the face" using terms like synapses and action potentials, while the dentist will focus on teeth and occlusion. This variation in meaning highlights the importance of context in diagnosis.

A deeper exploration of modern philosophy of meaning, such as Gottlob Frege's distinction between "extension" (all entities sharing a characteristic) and "intension" (attributes that define an idea), sheds light on how diagnostic errors may occur.

For example, "pain" is a broad term with high extension but low intension. However, focusing on specific pain types (dental implants, pulpitis, neuropathic pain) increases intension and reduces extension.

This shows how the vulnerability of medical language to semantic and contextual ambiguity can lead to significant diagnostic challenges.

Ambiguity and Vagueness in Medical Language

Ambiguity in medical language occurs when terms have multiple meanings, leading to errors and inconsistencies in diagnosis. Both ambiguity and vagueness are underexplored in clinical practice, despite their significant impact on clinical guidelines.

Doctors' interpretations of vague medical terms often differ, reducing uniformity in clinical practices compared to guidelines.

Ambiguity and vagueness are important concepts in understanding challenges in clinical communication and diagnosis. Despite being discussed in linguistic and philosophical contexts, they are underexplored in medical practice, with significant impact on clinical guidelines and diagnostic decisions.

Ambiguity occurs when a word or phrase has multiple meanings. In medical language, it can appear in several forms:

Syntactic ambiguity: When a sentence structure allows different interpretations. For example, "the pain is caused by inflammation" could mean that pain is directly caused by inflammation, or that inflammation is just one contributing factor.

Semantic ambiguity: Terms like "neuropathic pain" can refer to either peripheral nerves or the central nervous system, leading to confusion without further specification.

Pragmatic ambiguity: When the context does not provide enough information, such as when a doctor says "this is a suspicious diagnosis" without specifying which diagnosis is being considered.

Vagueness refers to cases where there is no clear distinction between categories:

Clinical vagueness: The term "fever" is vague, as a temperature of 37.8°C might be considered febrile for an immunocompromised patient but not for a healthy individual.

Diagnostic vagueness: A concept like "syndrome" is often vague, such as with chronic fatigue syndrome, where symptoms are general and markers are unclear, leading to varied interpretations by different physicians.

Clinical Implications: Ambiguity and vagueness can negatively affect adherence to clinical guidelines, causing diagnostic errors and inconsistent treatments. For example, "conservative management" can be interpreted differently by doctors, leading to discrepancies in patient care.

Examples:

Ambiguity: "Orofacial pain" could mean a temporomandibular disorder (TMD) to a dentist, but neuropathic pain to a neurologist, leading to different diagnoses and treatments.

Vagueness: The term "disease" varies depending on the context, such as hypertension being classified as a disease with organ damage, but seen as a manageable risk factor without complications.

This leads to inefficiencies in decoding the "machine message" transmitted by the system, as in the case of Mary Poppins' orofacial pain. Next, we delve into the concept of "encrypted machine language" in the subsequent chapters.

Encryption

Imagine a brain sending a message in machine language (wave trains, ion field packets), and that this carries a message like "Ephaptic," which must be decrypted to translate into verbal language. Both the patient, with epistemic vagueness, and the doctor, constrained by their field of expertise, contribute to the distortion of the machine's original message.

Often, the system's message remains encrypted until symptoms become severe enough for a diagnosis to be made.

«Why is the patient's key the REAL one?»
(Answer: Consider the Gate Control phenomenon.)

However, this concept brings our attention to an extraordinarily explanatory phenomenon called Gate Control. When a child is hit on the leg while playing soccer, in addition to crying, the first action they take is to rub the painful area extensively, to alleviate the pain. The child acts unconsciously, stimulating tactile receptors and closing the "gate" to the nociceptive entry of C fibers, thus reducing the pain; this phenomenon was discovered only in 1965 by Ronald Melzack and Patrick Wall..

In the case of encrypted language, much like in computers, the brain also encrypts and decrypts information. For example, researchers have explored how synaptic memory might be digitally stored in the brain.

Final Considerations

Language's role in diagnosis is a critical issue in medicine. The ICD-9 lists 6,969 disease codes, which increased to 12,420 in ICD-10. Studies estimate that diagnostic errors contribute to 40,000 to 80,000 deaths annually.

Charles Sanders Peirce's triadic approach—abduction, deduction, and induction—emphasizes that diagnostic errors often result from misinterpretations of clinical signs.

In this chapter, we shifted from discussing clinical signs to machine language and non-verbal signals. The next chapters will delve deeper into logic, time, and assembler codes.

Bibliography & references