The End of Diagnosis
The initial paradigm of clinical diagnosis was ontology, and pathology is renowned as the gold standard - either see or not see.
From the 17th to the 19th century, optical microscopes evolved toward the Abbe limit: they could reveal living tissue but not fine structure.
In the 20th century, optical and non-optical microscopes pushed beyond the Abbe limit. But the way to see structures and living tissue at the same time is indirect fluorescent labeling, and the vision-based ontology paradigm actually stalled.
Meanwhile, clinical diagnosis is undergoing a paradigm shift - algorithms.
Before the popularity of the Internet, the Department of Laboratory Medicine and the Department of Radiology were already independent. Numerical comparisons, data images, and physician judgments are like separation of powers.
Because the diagnosis is not directly ontology-based, the false positives and false negatives of these two departments are like ghosts - either unseen or shocked.
When the eye cannot see through the body, X-rays can.
When X-rays cannot provide tomographic, CT can.
When CT’s soft-tissue contrast is insufficient, MRI excels.
When MRI cannot capture dynamics, B-scan can.
The body has not been finished "vision"? The vision-based algorithm paradigm is close to stalling.
In Shanghai, China, between 1990 and 2015, only 11% of clinical diagnoses in 482 fatal medical dispute cases matched the findings from autopsies.
In the United States, approximately 795,000 people die or suffer permanent disability each year due to false-negative diagnoses, "The overall average diagnosis error rate was estimated at 11.1%."
By the way, autopsy is the gold standard of gold standards, and even it has an error rate.
The "low-hanging fruits" seemed to have all been picked, and people couldn't tell whether there were no fruits or they couldn't be found.
The advances in pathology, laboratory medicine, and radiology are reflected in more publications, increasingly complex analyses, and more expensive visualizations. Yet when we walk into our local hospital, many of these advances have not arrived.
The most despairing reality isn’t that more people flock to the vision-based paradigm in vain, but that its layers, reminiscent of a separation of powers, cannot be removed. More data, clearer images and older physicians often end up hindering progress.
If these elements cannot be integrated into a unified whole, we will need more Stoics to start anew from scratch.
The vision-based paradigm brings a creation day to clinical diagnosis, and when it stagnates, how can diagnosis avoid the end?
Independence Day for Paradigms
In the 18th century, Mikhail Lomonosov and Antoine Lavoisier each experimentally confirmed the conservation of mass.
Both believed they were studying chemistry, not physics.
Even a hundred years later, the physics world incorporated the conservation of mass into the thermodynamic framework, but could not prevent the independence of chemistry.
Paradigm expansion rarely originates from within the mainstream discipline, it begins with an independent declaration from the margins.
Although the ontological paradigm implies the gold standard, visual thinking has greatly influenced the product form of non-visual ontological paradigms.
Ultrasound, ECG, sphygmomanometer, thermometer, glucose meter, etc., were either absorbed by other departments in the 20th century or lack the ambitions of Lomonosov and Lavoise in the 21st century.
To avoid the end of clinical diagnosis, we need Independence Day for non-visual paradigms. Establish independent departments for different ontological paradigms.
AIolf creates out-of-the-box software and hardware tools as well as API platforms, advocating the use of olfaction to break through the limitations of vision.
We aim to shake and solve the Holy Grail problem. In cancer diagnosis, the process of olfaction can improve the structure of vision. In depression diagnosis, objective signals are expected to override subjective assessments.
We are addressing and assisting researchers in solving the following 10 problems, which will accelerate the independence of the Olfactory Department.
Meta-question: Do different cancers have different olfactory signals?
2. Do olfactory signals come from TME or the VOCs of specific substances?
3. Are there different olfactory signals for different subtypes of cancer?
4. Is there an olfactory inflection point in the process from inflammation to cancer?
5. When therapeutic interventions are applied to cancer, are there any causal changes in olfactory signals?
Meta-question: Does depression have olfactory signal?
7. Do olfactory signals come from the brain microenvironment or specific hormones?
8. Is there an olfactory inflection point in the process from health to depression?
9. Can olfactory inflection points diagnose depression?
10. When therapeutic interventions are applied to depression, are there any causal changes in olfactory signals?
The Birthday of Olfaction
It's harder to find 10 guys interested in olfactory paradigm diagnostics than it is to contact 10,000 experts who are skilled in visual paradigm diagnostics, and the healthcare industry is always resistant to new things.
Based on this, AIolf needs to do more than missionaries and believers.
We sponsor software and hardware tools, open API platforms, provide technical certifications for olfactory paradigm diagnosis, and improve the logic and methodology of the olfactory discipline, helping any medical organization on Earth that is preparing to establish an independent olfactory department to cultivate a talent pool.
Our next plan is to follow the independent guidelines below, from methodological validation to multi-center replication to clinical trials.
Any medical organization or industry partner is welcome to apply for the use of the AIolf GuGuSniff API to participate in verification and publish papers.
It is a hybrid model of the ontological paradigm and the algorithmic paradigm, and is moving towards clinical validation and consumer application.
When we win, more people will benefit from it!
Olfaction Department Independent Guideline 1.0
·Definition of olfaction: Olfaction is the electrical-signal mapping of a substance’s intrinsic molecular properties, distinct from sensory experience and traditional chemical quantitative analysis.
·Signal ontology: Olfactory signals should be explicitly traced to molecular properties (mass, polarity, vibrational spectra, etc.) that are transduced by an interface into electrical responses. Publish the experimental designs, methods, and validation results used to support these mappings to avoid attributing observed differences to random noise.
·Verifiable mapping: Publish a reproducible experimental chain framework (molecular properties → interface response → signal features → clinical labels) and provide causal validation results from pre- and post- intervention studies.
·Cross-center consistency: Publish unified sampling and calibration standards, threshold-definition methods, and multi-center blind-test pass rates (for example, target pass rate ≥ 90%).
·Independent information-gain assessment: Publish joint trials involving pathology, laboratory medicine, and radiology that report study design, conclusions, and performance metrics (such as gains in AUC, sensitivity, and specificity).
·Minimum detectable change: Publish the MDC decomposition methodology (an attribution framework for intrinsic change, transmission/sampling, interface, and noise), along with estimation methods and confidence intervals for each component.
·Clinical validation pathway: Publish clinical trial design essentials and conclusions, specifying the strength of evidence for how the olfactory paradigm improves diagnostic and therapeutic decision-making.