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| Telepathology can allow pathology images to be reviewed by qualified specialists in another location. Description: Illustration of digital pathology and remote specialist collaboration in a Nigerian healthcare setting. |
Getting a medical test done is only part of the diagnostic process. Someone with the right expertise must also interpret the sample, image or result correctly.
That can become difficult when specialist services are concentrated in major cities while patients and health facilities are spread across a much larger country.
This is one reason technologies such as digital pathology, telepathology and artificial intelligence (AI) are attracting attention in Nigeria and other parts of Africa. They form part of a broader transformation in which artificial intelligence is increasingly being explored in African healthcare.
Telepathology could allow a specialist hundreds of kilometres away to examine a digitised pathology image without the patient having to travel to the specialist's location. AI may assist with some parts of that process by helping trained professionals analyse large amounts of medical information or identify patterns that deserve closer examination.
But there is an important point to understand from the beginning:
AI should not simply be viewed as a replacement for doctors or pathologists. Its more realistic role is to support qualified health professionals while improving access, efficiency and consistency where the technology has been properly validated.
What is pathology?
Pathology is the branch of medicine concerned with understanding and diagnosing disease by examining tissues, cells, body fluids and other laboratory information.
A pathologist may, for example, examine tissue removed during a biopsy to help determine whether abnormal cells are present.
This makes pathology an important part of the diagnosis and management of many diseases, including cancers.
Laboratory testing is also fundamental to diagnosing and managing infectious diseases, although the tests and diagnostic pathways vary considerably between conditions. HIV, for example, has specific testing algorithms for determining HIV status, while newer approaches such as HIV self-testing are helping expand access to HIV testing in Nigeria.
Traditionally, a pathologist examines prepared tissue or cell samples using a microscope. Digital technology is changing what that workflow can look like.
What is digital pathology?
Digital pathology involves converting pathology material, particularly microscope slides, into high-resolution digital images that can be viewed and analysed on a computer.
Think about what happened when photography moved from physical film to digital images.
The underlying subject did not change, but digitisation made images easier to store, transmit, reproduce and analyse using computers.
A similar idea applies to pathology.
A properly prepared pathology slide can be scanned using specialised equipment. The resulting digital image can then be viewed on an appropriate computer system rather than only through the original microscope.
This creates another possibility: the person examining the image does not necessarily have to be in the same building where the specimen was collected.
That brings us to telepathology.
What is telepathology?
Telepathology is the practice of examining pathology information from a different location using telecommunications and digital technology.
Imagine a patient attends a health facility in a community where there is no resident pathologist.
A specimen may be collected and appropriately prepared at the facility. Depending on the system being used, images of the specimen can then be digitised and securely transmitted to a qualified pathologist somewhere else.
The specialist can review the material remotely and provide a professional interpretation.
In simple terms:
Patient or specimen at Facility A → digital pathology image → secure transmission → pathologist at Facility B → specialist report
AI is not required for this process.
That distinction matters because telepathology is primarily about providing specialist pathology expertise across distance, while AI involves computer systems performing particular analytical tasks.
The two technologies can, however, work together.
Where does artificial intelligence come in?
AI systems can be trained to recognise particular patterns in medical data.
Within digital pathology, appropriately developed AI tools may potentially assist with tasks such as identifying areas of an image that deserve closer inspection, counting or measuring certain features, classifying particular patterns, supporting quality-control processes or helping specialists manage large numbers of digital slides.
This does not mean that an AI system understands a patient's complete medical situation in the same way as a healthcare team.
Medical diagnosis frequently requires much more than recognising a visual pattern. Doctors may need to consider symptoms, examination findings, laboratory results, imaging, medical history and other clinical information before reaching a conclusion.
This is why the more useful model is often human plus technology, rather than human versus technology.
Why could telepathology matter in Nigeria?
Nigeria has large urban centres with specialist hospitals, laboratories and experienced medical professionals. But access to specialist services is not distributed equally across every community.
Distance creates a practical problem.
If a specimen or patient must travel long distances simply because specialist expertise is unavailable locally, diagnosis may become slower, more expensive or more difficult to obtain.
Telepathology could potentially change part of this equation.
A health facility does not necessarily need to have every specialist physically present if some expertise can be delivered safely and reliably from another location.
This reflects the wider development of digital health technologies for healthcare delivery, where digital tools can help connect patients, healthcare workers, information and services across geographical boundaries.
In August 2026, Nigerian diagnostic-sector discussions highlighted the potential for AI, telepathology and related technologies to expand access to specialist diagnostic services, particularly where specialist expertise is limited.
The idea is especially relevant in a country where specialist health professionals and advanced diagnostic services are not evenly distributed.
Could telepathology reduce diagnostic turnaround time?
Potentially, yes, but technology does not automatically make every diagnosis faster.
In a functioning digital pathology system, an image can be transmitted electronically rather than relying entirely on the physical movement of pathology material between locations.
That could shorten part of the diagnostic pathway.
However, turnaround time still depends on several other things: how quickly the specimen is collected and processed, the quality of slide preparation, availability of scanning equipment, connectivity, workload of the receiving specialist, laboratory information systems and how quickly reports reach the clinician responsible for the patient.
Well-designed electronic health records can also help ensure that relevant diagnostic information becomes part of a patient's continuing health record and is available to authorised healthcare professionals when needed.
A fast internet connection cannot compensate for a poorly prepared specimen.
This is an important lesson for digital health generally:
Technology can improve a health system, but it cannot replace the basic systems required to deliver good healthcare.
What could this mean for underserved communities?
This may be where telepathology has its greatest potential.
Instead of attempting to place every type of specialist in every facility, health systems can create networks in which appropriately equipped facilities connect with specialists elsewhere.
For example, a specialist working in Lagos, Ibadan, Abuja or another referral centre could potentially review suitable digital pathology material originating from a facility much farther away.
The patient benefits from access to expertise rather than simply access to technology.
That distinction is important.
The objective should not be to put computers into hospitals for the sake of digitisation. The objective should be to help people receive accurate diagnoses and appropriate care.
AI could also introduce new risks
Artificial intelligence is not automatically accurate simply because a computer produced the answer.
An AI system learns from data. If its training data are poor, unrepresentative or inappropriate for the population in which the system is being used, its performance may suffer.
There is also the possibility of automation bias, where a healthcare professional places too much confidence in a computer-generated recommendation simply because it appears precise.
Several questions therefore matter before an AI system is incorporated into healthcare.
Has the system been clinically validated for its intended purpose?
Does it perform reliably across the populations and equipment where it will actually be used?
Do healthcare professionals understand its limitations?
What happens when an AI recommendation and a pathologist's assessment disagree?
Who remains accountable for the clinical decision?
These are not reasons to reject AI. They are reasons to introduce it carefully.
Patient privacy is another major issue
Digital pathology can involve highly sensitive health information.
Once medical information is digitised and transmitted between facilities, protecting it becomes essential.
Healthcare organisations need appropriate safeguards governing who can access patient information, how information is transmitted and stored, how long it is retained and what happens if a system is compromised.
This is not unique to pathology. The same questions about privacy, security and authorised access arise when healthcare systems introduce electronic health records.
AI creates additional questions because some systems require large amounts of health data for development, testing and improvement.
Patients should not have to trade away privacy simply to benefit from better technology.
Strong data governance therefore needs to develop alongside digital healthcare.
What does WHO say about AI in healthcare?
The World Health Organization recognises that artificial intelligence has potential applications across diagnosis, treatment, health research, surveillance and other areas of healthcare.
At the same time, WHO has stressed the importance of appropriate governance.
Its guidance addresses issues including safety, effectiveness, transparency, accountability, privacy, equity and human oversight.
This matters particularly when an AI system influences medical decisions.
A system recommending entertainment and an AI system analysing information that could influence a person's medical care do not carry the same level of risk.
Errors in healthcare can have serious consequences.
AI systems used for medical purposes therefore require appropriate evaluation, validation, regulation and monitoring.
Will AI replace pathologists?
Predictions that AI will simply eliminate pathologists overlook how medical diagnosis actually works.
Pattern recognition is important in pathology, but the pathologist's job can involve much more than identifying patterns in an image.
Clinical context matters. Unusual cases matter. Quality assurance matters. Communication with other healthcare professionals matters. Professional judgement and accountability matter.
AI is therefore better understood, at least for now, as a potential diagnostic support tool.
It might help a pathologist work through particular tasks more efficiently or draw attention to areas requiring closer examination. The final clinical process still requires qualified professionals and appropriate safeguards.
The strongest healthcare systems of the future may therefore not be those that choose between doctors and AI.
They may be those that determine which tasks humans perform best, which tasks computers can safely assist with and how the two can work together.
What Nigeria would need to make telepathology work
Buying scanners and AI software would not be enough.
Successful telepathology requires a functioning ecosystem.
Nigeria would need reliable laboratory processes, appropriate digital pathology equipment, trained laboratory professionals and pathologists, dependable power and connectivity, secure information systems, interoperability where different systems need to communicate, quality-assurance procedures, clear professional responsibilities, sustainable financing and appropriate regulation.
Solutions also need to reflect local realities.
A technology designed around uninterrupted electricity, extremely fast internet and expensive infrastructure may perform impressively in one health system while being impractical in another.
Nigeria therefore needs digital-health solutions designed around the environments in which they will actually operate.
The bigger opportunity for African healthcare
Telepathology illustrates a broader opportunity for digital health across Africa.
Technology can help move expertise without always moving the expert.
A specialist can potentially support multiple locations. Health information can move more quickly between appropriate parts of the health system. Digital records can reduce fragmentation when systems are properly designed. Remote consultation can connect patients and health workers with expertise that may otherwise be difficult to reach.
Telepathology is only one example. Our broader guide to Artificial Intelligence in African Healthcare examines other potential applications of AI as well as the risks and limitations that African health systems need to consider.
The same principle applies across these technologies:
Digital health is valuable when it solves a genuine healthcare problem.
The bottom line
Telepathology could help Nigeria address an important challenge: specialist medical expertise is not equally available everywhere.
By allowing pathology material to be digitised and reviewed remotely, health facilities may be able to connect patients with specialists located elsewhere.
Artificial intelligence could add another layer by assisting professionals with particular analytical tasks, prioritisation or quality control.
But AI is not a shortcut around the fundamentals of healthcare.
Accurate diagnosis still depends on good specimens, functioning laboratories, properly validated technology, trained professionals, clinical judgement, patient privacy, quality assurance and effective regulation.
The most useful question is therefore not whether AI will replace Nigerian doctors.
It is this:
How can Nigeria use digital technology to help qualified healthcare professionals deliver reliable specialist care to more people, regardless of where those people live?
That is where telepathology could make a meaningful difference.
Frequently Asked Questions
What is telepathology?
Telepathology is the remote examination of pathology information using digital and telecommunications technology. It can allow a qualified pathologist in one location to review suitable pathology material originating somewhere else.
Is telepathology the same as artificial intelligence?
No. Telepathology connects pathology services across distance. AI refers to computer systems capable of performing particular analytical tasks. A telepathology service can operate without AI, although AI tools can potentially be incorporated into digital pathology workflows.
Can AI diagnose diseases without a doctor?
Some AI systems can perform specific medical analytical tasks, but this should not be confused with independently managing a patient's complete diagnosis and care. Medical decisions often require clinical context, professional judgement and human oversight.
Can telepathology help rural hospitals in Nigeria?
Potentially. Properly implemented telepathology could connect facilities without local pathology expertise to specialists elsewhere. Its effectiveness depends on specimen quality, equipment, connectivity, trained personnel, secure data systems, regulation and sustainable financing.
Is AI in healthcare safe?
AI can be useful, but safety depends on how a particular system was developed, validated, regulated and used. Healthcare AI should be evaluated for its intended clinical purpose and should include appropriate professional oversight.
References and Further Reading
World Health Organization. (2021). Ethics and governance of artificial intelligence for health: WHO guidance.
https://www.who.int/publications/i/item/9789240029200
World Health Organization. (2023). Regulatory considerations on artificial intelligence for health.
https://www.who.int/publications/i/item/9789240078871
World Health Organization. (2024). Artificial Intelligence for Health.
https://www.who.int/publications/m/item/artificial-intelligence-for-health
Dania, O. (2026, August 11). AI, telepathology revolutionising healthcare diagnostics in Nigeria – Cerba-Lancet CEO. Punch Nigeria.
https://punchng.com/ai-telepathology-revolutionising-healthcare-diagnostics-in-nigeria-cerba-lancet-ceo/
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