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четверг, 23 апреля 2026 г.

Julius Caesar's Health Debate Reignited: Stroke Or Epilepsy?

 


People look at the head of a statue depicting Julius Caesar (100BC- 44BC) as they visit the the exhibition entitled 'the myth of Cleopatra' on April 9, 2014 at the Pinacotheque in Paris. (Photo credit ERIC FEFERBERG/AFP/Getty Images)


"He was of spare habit, had a soft and white skin, suffered from distemper in the head, and was subject to epileptic fits, a trouble which first attacked him, we are told, in Corduba." -- Plutarch's Life of Caesar 17.2

Famous words from the Greek historian Plutarch have offered tantalizing clues to the causes of Julius Caesar's ill health prior to his assassination on the Ides of March 44 BC. But Plutarch was born long after Caesar's death, and his writing in particular has been interpreted a number of ways over the past two millennia.  Caesar had migraine headaches. Or hypoglycemia. He had a tapeworm in his brain. Most commonly, he has been diagnosed with morbus comitialis, the Latin term for epilepsy.

Francesco Galassi and Hutan Ashrafian have been fascinated by the ancient world since childhood.  The medical doctors, who practice at Imperial College London, have proposed a new diagnosis based on their reading of the ancient sources: cardiovascular disease causing strokes. Galassi told me that they are "reconsidering the very Greco-Roman sources philologically and medically, liaising with experts in the field in Italy, the UK, and the US" to better understand Caesar's health. "We refuse to accept a priori the diagnosis of epilepsy."

Epilepsy in ancient Rome was well known and its symptoms often reported. Galassi therefore thinks that there should be more numerous accounts of Caesar's epileptic episodes in historical records if he truly suffered from it. By combing through the ancient literature, Galassi and Ashrafian have come to a different interpretation of Caesar's reported symptoms.

In a letter to the editor of Neurological Sciences published last month, Galassi and Ashrafian explain their reevaluation. "Together with the symptoms of headache, vertigo and falls as a possible result of limb paresis, gait disturbance, sensory deficit or syncopal episode can be considered in terms of cerebrovascular insults and stroke," they write, and depression and personality changes Caesar suffered "may also be consistent with cerebrovascular disease."

As doctors, Galassi and Ashrafian know that a good medical and family history is key to understanding a person's health. Pliny the Elder mentions the sudden death of Caesar's father and another close relative, which can easily be associated with "cardiovascular complications of stroke episode or a lethal myocardial infarction." If Caesar's relatives died of a heart attack, it is reasonable to question the dictator's symptoms in light of a possible family history of cardiovascular issues. Galassi says that "we think the TIAs [transient ischemic attacks or mini strokes] started at the end of his life; likely in 46 BC or a littler earlier."

Barry Strauss, a Cornell University military historian whose book The Death of Caesar represents the latest research into the dictator's life, told me that, while he finds the cardiovascular theory intriguing, he is not convinced. "Caesar's illness is said to have begun in Cordoba, Spain," Strauss says, referencing Plutarch, "which would suggest a specific event such as head trauma."  Traumatic head injuries can cause neurological problems, and since Caesar is reported to have recovered quickly from each episode, Strauss finds a diagnosis of epilepsy more convincing.

If Julius Caesar was suffering from mini strokes, as Galassi and Ashrafian believe, why would his problems be documented as epilepsy?  It is not necessarily the case that ancient historians did not understand the disease.  Rather, Galassi and Ashrafian suggest that "Caesar and his adopted son Octavius may have contributed to the diagnosis of epilepsy, as this was considered a 'sacred disease'." It may have made Caesar look more powerful and more divine, shoring up his public profile and ensuring his eventual deification. But Strauss counters that "it was not to Caesar's advantage to admit that he had epilepsy because Romans considered epilepsy to be a bad omen and the Hippocratic Greek corpus denied that epilepsy was a sacred disease."

Deification of Julius Caesar. Engraving by Virgil Solis for Ovid's Metamorphoses Book XV, 745-850. (Public domain image via Wikimedia Commons)

In the end, Caesar's diagnosis may not be a case of either/or. Strauss notes that in researching his book, he learned from neurologists that strokes and head trauma are both risk factors for developing epilepsy later in life. "Caesar could have had both epilepsy and transient ischemic strokes," Strauss says.  Did cardiovascular disease cause strokes that in turn caused epileptic episodes? Did Caesar suffer a blow to the head in Cordoba that resulted in epilepsy? Considering that even with modern medical technology there is no test that can confirm or rule out epilepsy, Strauss points out "we can't be sure about a diagnosis 2,000 years after the fact."

Reanalysis of ancient diseases is not a new phenomenon, and with staggering advances in medical technology recently, both medical doctors and archaeologists are learning more about disease in the past. Research into the lives and deaths of King Richard III or Ötzi the Iceman would not have been possible a couple decades ago. The difference between these men and Julius Caesar, though, is that their skeletons were found intact. As Caesar was cremated following his assassination, there is little hope of bioarchaeologists finding his mortal remains and poring over them for additional clues to his health. We may be debating about one of the most powerful figures in history for a long time to come.


https://tinyurl.com/3cnyefyf

вторник, 12 февраля 2019 г.

This AI-driven microscope from Google could help detect cancer in future

Google showcased its prototype Augmented Reality Microscope (ARM) platform with a new modified light microscope that can detect breast cancer metastases as well as prostate cancer.


Google showcased its prototype Augmented Reality Microscope (ARM) platform with a new modified light microscope that can detect breast cancer metastases as well as prostate cancer.


Google showcased its prototype Augmented Reality Microscope (ARM) platform with a new modified light microscope that can detect breast cancer metastases as well as prostate cancer. The microscope, powered by Artificial Intelligence (AI) and machine learning algorithms enables real-time analysis. It displays the results directly into the field 0f view, unlike traditional analog microscopes that are need users to view the sample through the eyepiece. The magnifications can be between 4-40x and the result is displayed by outlining detected tumor regions with a green contour.


The prototype was showcased during a talk delivered at the Annual Meeting of the American Association for Cancer Research (AACR), with an accompanying paper “An Augmented Reality Microscope for Real-time Automated Detection of Cancer” which is currently under review. The move is aimed at accelerating the adoption of deep learning tools for pathologists globally. Google’s ARM platform can be retrofitted into existing light microscopes as well, which requires low-cost components. The microscope offers several visual feedback, thanks to machine learning algorithms. This includes text, arrows, contours, heatmaps, or animations.
“While both cancer models were originally trained on images from a whole slide scanner with a significantly different optical configuration, the models performed remarkably well on the ARM with no additional re-training,” reads a Google blog post. “Of course, light microscopes have proven useful in many industries other than pathology, and we believe the ARM can be adapted for a broad range of applications across healthcare, life sciences research, and material science,” the post added.


пятница, 27 июля 2018 г.

Sherlock in Health: How artificial intelligence may improve quality and efficiency, whilst reducing healthcare costs in Europe


Summary






Various megatrends are impacting healthcare systems in Europe, creating a scenario where artificial intelligence based technologies could be deployed for the benefit of all stakeholders. Converging of these trends, such as, aging of the population in the region, the resulting high cost of healthcare, coupled with patients becoming more demanding and value-focused, is creating a situation where technology can help in improving healthcare access, quality and affordability. It is not hard to imagine a future with intelligent technologies helping us diagnose diseases faster, and assisting doctors in treatment decisions, armed with evidence based analysis of likely outcomes.

AI is increasingly becoming a part of the healthcare ecosystem. Some of the applications developed, though in early stages, are having an impact across care pathways, starting at prevention, to diagnosis, treatment and recovery. At this stage, it is very important to analyse the demand and potential benefits from AI applications in healthcare in Europe. This will not only help us distinguish between realistic hopes and unrealistic hypes, but will also help in focusing our efforts in the right areas.

Analysing demand and potential benefits throughout healthcare is very complex and many factors come into play. We looked into three care pathways as a representation of both the benefits that might accrue from AI use in healthcare and the medical dilemma’s it will create. We estimate that large-scale AI use could yield benefits of the following magnitude.

     For childhood obesity: AI use could yield cost saving of up to EUR 90 billion over the next ten years. This saving estimate includes benefits from lower medical costs, and reduced losses from lower productivity and sick days. AI could also help in increasing the efficiency of self-monitoring for preventing obesity.

     For diagnosis of dementia: AI use could help save up to EUR 8 billion in diagnosis cost over the next ten years, largely driven by increased rate of diagnosis at primary care level. AI can help diagnose with up to 90 percent accuracy, bringing it to a large proportion of dementia patients who never receive a formal diagnosis.

     For diagnosis and treatment of breast cancer: AI use for diagnosis and treatment of breast cancer could be very helpful in early detection, also helping in treatment decision making and reducing doctors’ direct engagement in potentially repetitive tasks. It could help save up to EUR 74 billon over the next ten years, if used on a large scale.

However, achieving these benefits will not be easy. Various challenges exist, such as lack of sufficient data, enabling data standards and regulations. According to various experts we interviewed, technical, legal and financial feasibility of adopting AI will be critical. Equally important, will be to assess the psychological feasibility – is the public actually ready and receptive to AI adoption in health? Based on our analysis

of constraints and interviews with industry experts, we make three recommendations to help improve technology-driven healthcare services in Europe.

     Introducing a balanced scorecard in policy making will ensure that the focus is not restricted to any one policy area, such as: improving the quality of healthcare; containing the cost of care; or managing overall population health.

     Moving quickly and consistently on regulations will ensure that the vision on AI within the healthcare industry is matched and supported by timely regulations.

     Redefining reimbursements to support outcome based care will alleviate any payer related concerns for providers and patients, providing the much needed development boost to AI tools.

Introduction






Access to quality and affordable healthcare is a challenge that is growing every day. Increasing demand and increasing scarcity of health care personnel has put pressure on healthcare delivery, which is in constant need of optimisation. According to data collected from several EU nations, medical errors and healthcare related adverse events occur in eight to twelve percent of hospitalisations. Preventing such mistakes could help to prevent more than 3.2 million days of hospitalisation each year within the EU1.

Technological breakthroughs in artificial intelligence and the availability of big data present the promise of reducing such errors, whilst making healthcare more accessible and affordable. Artificial intelligence will not completely replace physicians and care workers, but it can play a key role in reducing the pressure on healthcare systems and be a decision supporting tool for physicians.

In this paper we assess the healthcare landscape2 in Europe3 and its readiness for artificial intelligence (AI) applications. We also estimate the probable benefits of using AI applications in healthcare, based on three different but interrelated dimensions: potential cost savings to patients; rise in efficiencies in healthcare services; and the increase in accessibility of healthcare services. Furthermore we analyse three conditions and associated care pathways:

    Prevention of childhood obesity;

    Diagnosis of dementia; and

    Diagnosis and treatment of breast cancer

Based on the analysis, we identify some major challenges and the following steps needed, in order to begin moving to large-scale AI adoption and advanced healthcare.



1    http://www.euro.who.int/en/health-topics/Health-systems/patient-safety/data-and-statistics

2    AI will have an impact on all health related fields including healthcare services, pharmaceuticals, and life sciences. For this study, we are only looking at the potential impact on healthcare


3    The geographical scope of the study covers Europe. Interviews have been conducted in Austria, Germany and the Netherlands





























суббота, 10 декабря 2016 г.

Will Physicians Become Obsolete?




Will that target market soon become obsolete in the choice of medication and other services?
Maybe not entirely, but from the work we are doing using AI to create data-driven patient treatment decisions for specialist physicians, it is now becoming clear that at least 80% of physician work, if not more, will become obsolete in the future, and potentially the near future, with the advent of the tricorder already in trials this month.
Current approaches to diagnosis
Currently, a large amount of patient diagnosis is done by ‘Dr Google’. Although it is far from perfect, given most conditions have a large variety of symptoms in common, other work in the area of accurate diagnosis is rapidly increasing.
Let’s consider how specialists diagnose at present. Firstly, they get patient history, then the physicians may order some tests based on their memory of what they learned as well as a large amount of drug advertising and PR. The impact is that the treatment is inferior to what it could be, as humans are fallible, and patients often die unnecessarily as a result.
One study in the US (by Johns Hopkins) found that 40,500 patients die each year in ICU as a result of misdiagnosis. To put this in perspective, this is equivalent to the number of deaths from breast cancer. However, this is not to place blame on the physicians as they are in a difficult situation with hundreds of thousands of different conditions that have similar symptoms, at least 8, 000 ultra rare conditions that most doctors would never be exposed to, plus thousands of updates in each medical area every week. It is physically impossible for physicians to stay up-to-date in most areas, but especially in rapidly progressing ones such as oncology.
A study in Oncology pitted AI diagnosis against a panel of four leading oncologists wherein both sides examined patient scans and made a diagnosis around tumor progression. The AI outperformed the human diagnoses by a significant margin.
Just to clarify, given some people have been calling some things ‘AI’ and they are not. This study was, of course, using real Artificial Intelligence – not simply expert medical systems that are clinical pathway and expert clinical support systems which occasionally erroneously label themselves as ‘artificial intelligence’ because it is a buzz word. The expert clinical support systems are very rule-based and simplistic and cannot take in the complexity that is required in today’s oncology work with complex patient profiles, in comparison to what a real Artificial Intelligence (a combination of machine learning, deep learning and evolutionary computation) can do.
A lot of what physicians currently do - including testing, diagnosis and treatment decisions - can actually be done better by active data collection and collation, sensors, and AI analytics. Physicians are meant to consume all those data points and consider it in the context of the latest medical literature and the patient history, and make decisions in the best interest of the patients’ health outcome.
It actually is physically impossible for physicians to consume all the latest information and integrate it constantly. For example, how many cardiologists can digest all of the latest 5000+ articles and research updates on oncology on a weekly basis and still do their job? It is an impossible task.
Is Artificial Intelligence the future of diagnosis?
So, is Artificial Intelligence the future of diagnosis? Artificial Intelligence can pull data from trillions of data points in a second, analyze all relevant factors and come up with a far more accurate conclusion than a human brain is capable of, as the studies in this area have already shown. Now that we are in the era of personalized medicine, utilizing far more complex models with thousands of baseline and multi-omic data points, up-to-date data and data capture are critical to make the most advanced treatment decisions.
Of note is that Eularis are currently working on an Artificial Intelligence driven clinical platform for oncologists to do the following:
• Review all relevant, authoritative medical literature in oncology and collate it,
• Review all clinical trial data in the space and collate it with results, biomarkers and more
• Add in local country and hospital treatment protocols,
• Link this to the electronic patient records (longitudinal data) to examine scan images, all blood and diagnostic test results (including genetic testing) along with treatment and patient outcomes,
• Collate all that constantly updated data to allow the Artificial Intelligence to identify what treatment will have the best possible outcome for a specific unique combination of factors for a specific patient
We are doing this in oncology currently but could equally take this wider into other spaces in the future.
New technologies will allow physicians to work faster and improve their work as all the data can be taken into account – something that is simply not possible currently with all the constant increases in data. In the future, technology will replace the diagnosis component of medicine, which means that fewer doctors will be needed.
All diagnosis and treatment plans will be Artificial Intelligence powered; the physicians will provide the care. These systems will take time to perfect but they are already pretty good. Soon, like all technology, no doubt, they will become commonplace and cheap, and all people will have diagnostic systems at home. Think back to the days when computers were big room-sized objects, and Bill Gates is remembered for saying that 640K was more than anyone would ever need. Now we have more than that on our phones, let alone our computers.
The future is almost here
Inspired by the Tricorder in Star Trek, which was how the Starship doctor performed his medical examinations (by moving the device over the patient’s body and getting a full reading of everything going on), this technology is almost a reality now. The Qualcomm Tricorder XPRIZE is a competition to develop this device with a $10 million prize for the best device – which will be a handheld device like the original in Star Trek. The first user tests started in September 2016. They are around capturing key health metrics, and at this early stage are expected to diagnose 13 health conditions. The winner will be announced in the next few months. This device signals the beginning of a new era of healthcare diagnosis. The breadth and range of conditions will, no doubt, be added to regularly with more - and improved - features.
Conclusions
We are living in a very interesting era where technology is changing a lot of areas in medicine. This has implications not only for physicians, patients and health outcomes, but also for pharmaceutical companies and their traditional ways of marketing and selling products. In pharma, we have all heard about ‘lip service’, ‘patient-centricity’ and ‘beyond the pill’. However, the challenges in our environment now are forcing these changes more rapidly than those in pharma may even be aware.

For more information on these topics and how you can get involved in the next generation of medicine, contact Eularis at: http://www.eularis.com