Can Artificial Intelligence Replace Humans in Histopathology?

    Convolutional neural networks (CNNs) have been an important component in the development of artificial intelligence (AI) and machine learning. It has been used in interpreting visual and spatial data and is being trained to perform in tasks related to image recognition, language processing, and tasks in the medical field (ScienceNewsToday). Delving into the medical field, pathology is a specialty that involves histology, which means studying tissue samples under a microscope to determine if the tissue is diseased. As artificial intelligence such as CNNs continue to evolve, it begs the question, can they replace humans in histopathology?

    During Dr. Baker’s talk at Loyola, he highlighted his own research regarding how deep convolutional models (DCNNs) struggle with the configuration of images compared to humans. In his paper, Dr. Baker highlighted how DCNNs focused more on color and texture than humans do (Baker). Additionally, in his presentation he went into detail into how the AI struggled with recognizing an image based on manipulation of the images’ border. For example, if the AI was given the silhouette of a cat, but if the border was turned into rigid edges rather than the normal “smooth” border, it would have more trouble recognizing what the image was in comparison to an image that was “Frankensteined” (chopped up and put together in a different configuration).

    It is necessary to make note of this distinction in the AI’s recognition of the image because cell tissues do not always maintain a constant shape or look, meaning that Dr. Baker findings could pose an issue of accuracy when using AI in pathology. A review article by Prasad et al. delves further into the use of AI in the field of histopathology. In their findings, CNNs were found to have consistent results in detecting and classifying cancerous tissue and had levels of accuracy similar to trained pathologists in controlled settings (Prasad). However, the article highlights an issue in which AI systems struggle with variability in staining, slide preparation, and tissue morphology (Prasad).

    This connects to Dr. Baker’s findings, as the AI relies heavily on texture and color rather than truly understanding structural features, which limits the effectiveness of CNNs when analyzing histological samples that are inconsistent or irregular (Baker). Furthermore, Prasad et al. highlight that while AI can assist with lowering workloads and increasing efficiency, as mentioned, it still lacks the adaptability needed to analyze irregularities that can be common in complex histopathological cases (Prasad). This shows that while AI can become an assistive tool in histopathology, its limitations in image interpretation demonstrate that humans in pathology are still necessary. However, rather than replacing pathologists, AI is more useful as a supportive tool that enhances accuracy and efficiency.

 

References

Editors of ScienceNewsToday. (2026, April 7). Convolutional neural networks: the science behind modern artificial intelligence. Science News Today. https://www.sciencenewstoday.org/convolutional-neural-networks-the-science-behind-modern-artificial-intelligence#google_vignette

Baker N, Elder JH. Deep learning models fail to capture the configural nature of human shape perception. iScience. 2022 Aug 11;25(9):104913. doi: 10.1016/j.isci.2022.104913. PMID: 36060067; PMCID: PMC9429800.

Prasad P, Khair AMB, Saeed M, Shetty N. Artificial Intelligence in Histopathology. J Pharm Bioallied Sci. 2024 Dec;16(Suppl 5):S4226-S4229. doi: 10.4103/jpbs.jpbs_727_24. Epub 2025 Jan 30. PMID: 40061791; PMCID: PMC11888715.

Peripheral Nerve Degeneration: How the Shock Affects Nerve Repair

     In science, there has been an uptick in the use of electrical stimulation to "biohack" our bodies and brains, whether it is to wake us up or for physical therapies. As a result, many new studies have emerged to understand the body's natural stimulation and create tech that mimics it to address a variety of issues. Currently, scientists are digging deeper to determine which frequencies are the best for humans to create devices specifically for nerve degeneration.   

         During our class, we heard from Dr. Vincent Chen, whose focus was Power Spectral Density (PSD). PSD describes the power of a time-domain signal, or how a random process can be distributed across different frequencies. Chen's hypothesis is as follows: we should manipulate the waveform shape to target NMDA and AMPA receptors, which act as switches that turn on nerve growth. His clinical success with "random noise" stimulation is due to the rich PSD. He also questions modern electrical stimulation methods, as square waves commonly used contain harmonics, echoes of higher frequencies hidden within the signal. With these higher frequencies, it makes it harder to determine which signal is most optimal for nerve regeneration actively. Just following the frequency to him is imprecise because the signal will degrade as soon as it passes through the skin and tissue. He notes that the nerve membrane acts as a capacitor, resisting sudden changes, so changing the type of wave could also affect the nerve differently.  By controlling the voltage gradient, he can target very specific receptors. Chen's approach is highly specific, and with the future of implantable devices, it blows all past nerve studies out of the water.   

A different study conducted by Dr. Lingmei Ni uses very traditional electrical stimulation approaches to alleviate the effects of nerve damage. Ni uses multiple types of electrical stimulation, including NMES (neuromuscular), and low-frequency pulses to contract the muscles, helping prevent muscle atrophy directly. TENS is transcutaneous, blocking the pain signals with varying high and low frequencies. FES is the functional frequency, which can help paralyzed limbs return to function. These therapies have been used for a long time, but Ni has clinical data on specific frequencies to support her statement. Her studies show that 1 hour of 20Hz stimulation is proficient to accelerate axon growth after carpal tunnel surgery. Electrical stimulation increases BDNF and cAMP, which act as fuel for a growing neuron. However, even Dr. Ni points out how there is no standard for electrical stimulation. It varies between patients, parts of the body, and at times can seem almost random.   

These studies, when read together, can be seen as the future of electrical stimulation. Dr. Ni has a wide breadth of knowledge and clinical data on electrical stimulation, helping regenerate axons faster. Dr. Chen takes it one step further; no longer will the frequency or even type of wave vary from person to person. Rather, using PSD data, we can build stimulators that do not cause nerve fatigue or unwanted pain from high-frequency harmonies. With this amalgamation of information, other scientists can take this data to build more biohacking devices to help humans live more comfortable lives following nerve degeneration.   

Chen, VincentC.-F., et al. "Accelerating Peripheral Nerve Regeneration Using Electrical  Stimulation of Selected Power Spectral Densities." Neural Regeneration Research,  vol. 17, no. 4, 2022, p. 781, https://doi.org/10.4103/1673-5374.322458.  

Ni, Lingmei, et al. "Electrical Stimulation Therapy for Peripheral Nerve Injury." National  Center for Biotechnology Information, U.S. National Library of Medicine, 23 Feb.  2023, pmc.ncbi.nlm.nih.gov/.  

Mirco-coil Stimulation

    Electrode stimulation, such as deep brain stimulation (DBS), has been utilized in treating pain, seizures, and improving movement. It is achieved by directly applying an electrical pulse to neural tissue via a surgically implanted electrode. There have been numerous successes in treatments involving electrode stimulation. However, there are also risks and limitations such as inaccurate neural targeting, potential for tissue damage which may trigger inflammation and immune responses, and corrosion, though rarely, of the electrode itself.

    A new magnetic stimulation technique that aims to improve and reduce the limitations of current electrode and magnetic stimulation techniques is micro-magnetic stimulation (µMS). µMS has been found to have improved specificity of neural stimulation, it utilizes biocompatible materials that reduce inflammation and allow for deep brain stimulation without damaging neural tissue.

    I recently had the pleasure of attending a talk by Dr. Ye Hui, a biomedical engineer focusing his research on electromagnetic stimulation. His talk focused on his recent paper: “Restore axonal conductance in a locally demyelinated axon with electromagnetic stimulation.” This paper investigated a demyelinated axon model built in NEURON under circular micro-coil stimulation. Demyelinated axons are often the result of neurodegenerative diseases, ischemic injuries, among other factors. Due to demyelination, neural signals are blocked or slowed depending on the severity of the demyelination. But how to restore those neural signals is not fully understood. The main findings of Dr.Ye’s paper found that subthreshold micro-coil stimulation, which is just below the needed stimulus to generate an action potential, combined with the depolarization of an action potential was enough to restore axonal conductance. In other words, a subthreshold stimulus saved the incoming action potential by giving it the boost to get past the demyelinated area and continue down the axon. Restoration was dependent on the amplitude and frequency of the stimulus which was found to have the most consistent results at 5000Hz. Dr.Ye’s research provides vital insights into not only the development of micro-coil stimulation, but also in treatments of focally segmented demyelination cases.

    An article titled: “Micro-Coil Neuromodulation at Single-Cell and Circuit Levels for Inhibiting Natural Neuroactivity, Neutralizing Electric Neural Excitation, and Suppressing Seizures.” by Kim et al., investigates µMS in both research and therapeutic applications. While Dr.Ye’s paper focused on restoring axonal conductance, this article focuses on precise neural inhibition, which is similarly not well understood, with µMS. Using cortical in vivo two-photon imaging, the researchers were able to find that µMS suppressed single cells and increasing µMS magnitude further increased the number of inhibited cells. µMS was also found to be able to suppress hyperactive neural firing caused by pharmacologically induced seizures, with more research, this could potentially lead to the suppression of epileptic seizures. These findings emphasize the importance of further researching the potential applications of µMS technology in clinical settings.

    As this is still a new field of research, there is still much that is not known about µMS.  However, both Dr.Ye, Kim et al., and many others are paving the way for µMS. One of the most compelling aspects of µMS research are its increasingly promising applications to not yet well understood branches of neuroscience. With its application to restoring axonal conductance in locally demyelinated axons to suppressing seizures, µMS has the potential to become a treatment for a variety of neurological disorders.

Citations: 

Ye, Hui et al. “Restore axonal conductance in a locally demyelinated axon with electromagnetic stimulation.” Journal of Neural Engineering vol. 22,1 016042. 14 Feb. 2025.

Ye, Hui et al. “Improving focality and consistency in micromagnetic stimulation.” Frontiers in computational neuroscience vol. 17, 1105505. 2 Feb. 2023.

Kim, Kayeon et al. “Micro-Coil Neuromodulation at Single-Cell and Circuit Levels for Inhibiting Natural Neuroactivity, Neutralizing Electric Neural Excitation, and Suppressing Seizures.” Advanced science (Weinheim, Baden-Wurttemberg, Germany) vol. 12,22 (2025): e2416771.

When a Concussion “Heals”, Is the Brain Really Back to Normal?

One of the most striking points for a talk I attended this semester on concussion was the idea that recovery is not always as complete as it seems. Dr. Jennifer Krizman explained that even after someone is medically cleared and their symptoms have resolved, subtle effects on the brain function, especially memory, can persist. This challenged the common assumption that once a concussion is “healed”, the brain automatically returns to its pre-injury state. 

This idea has become increasingly relevant in recent years as concussion awareness has increased. Current research supports this, underscoring that individuals who have had concussions may still experience issues with memory, attention, processing speed, and sleep. Even “mild” concussions can lead to lingering effects years after the injury (Denworth, 2024). This article also highlights research showing structural changes in the brain long after the concussion, supporting that the traditional symptom-based evaluations aren’t always enough to assess long-term memory. 

Dr. Krizman’s talk made a very similar point: the brain doesn’t always recover completely just because a person’s symptoms have resolved. Memory issues can be subtle and easily overlooked, especially when someone feels physically fine. This corresponds with what the Scientific American article describes as the long tail of concussion effects. This is where difficulties such as memory lapses or concentration problems can present even when other symptoms resolve (Denworth, 2024). 

Emerging research is now using more sensitive brain-based measures to track recovery. For instance, a 2025 study reported that athletes who have suffered a concussion still showed changes in brain-blood flow and structure for up to a year after they were medically cleared. These changes occurred in areas of the brain involved in thinking and memory, suggesting that even when symptoms have faded, the brain may not have fully regained its pre-injury state (American Academy of Neurology, 2025). This helps us understand why some people continue to have memory lapses or difficulty concentrating long after they feel “normal”. 

Understanding that the brain changes can shift our thinking of concussion as a short-lived injury that fully heals in a few weeks, it may be more accurate to view them as injuries that leave lasting changes in brain function. This understanding could have real-world impacts on how athletes and patients are monitored during and after their concussions, possibly even a recovery plan may be needed that extends beyond symptom resolution. 

To conclude, recognizing that brain changes may persist even after people feel physically better can lead to better guidelines for return-to-play, return-to-learn, and long-term monitoring. Research has validated the experience of people whose memory and cognitive performance remain altered and impaired after concussions; without such research, these accounts might be overlooked and dismissed because patients’ symptoms appear to be “gone”.

References:

Denworth, L. (2024, November 19). Concussions Are Remarkably Common and Can Cause Long-Term Problems. Scientific American. https://www.scientificamerican.com/article/concussions-are-remarkably-common-and-can-cause-long-term-problems/ 

American Academy of Neurology. (2025, March 14). Do brain changes remain after recovery from concussion?. ScienceDaily. Retrieved February 27, 2026 from www.sciencedaily.com/releases/2025/03/250312190835.htm