Key summaries

"Key summaries" is a series of easy to understand articles aimed at non-experts. The articles summarise papers published in 4open and highlight and present key ideas and findings in a clear and concise way. Readers can then access the full text of the original paper at the end of each "Key summaries" article. "Key Summaries" articles are brought to you in collaboration with SciencePOD.

Sun-drying system could boost nutritional and medical value of a popular Mexican food

4open study reveals how sunshine and technology could promote wider use of prickly pear cactus

Capturing the sun’s energy to dry prickly pear (Opuntia ficus-indica) opens up a cheaper and more effective route to producing Opuntia powder with greatly improved nutritional value, new research published in the open access journal 4open shows.

“We are making a bioproduct of superior quality at much lower cost than traditional combustion-based technology,” says Mario Pagliaro of Italy’s Research Council. Pagliaro is a co-author of the paper which describes an innovative system for processing the leaves of the Opuntia cactus.

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Using artificial intelligence to predict the success of laser eye surgery

Algorithms modelled on biological neural networks can predict whether patients will need further corrective treatment, study shows

What if you knew that a medical procedure you intended to have was likely to be unsuccessful? What if your doctor could change things before the procedure to maximize the chance of success, specifically for you?

Now, researchers have developed an algorithm that can predict whether one of the most common surgical procedures – laser eye surgery – will be successful in a given patient. The technique, described in the study “Using Neural Networks to Predict the Outcome of Refractive Surgery for Myopia” in open-access journal 4Open, could allow surgeons to tailor the procedure for each patient to maximize the chances of success.

Predicting success

For most patients, laser eye surgery for nearsightedness is effective and safe. However, a small percentage of patients do not experience a successful outcome and require subsequent corrective treatment.

Before many medical procedures, a doctor can give a patient a general idea of the chances of success. However, these success rates are often based on the general population and typically don’t reflect an individual patient’s chances.

In fact, given the number of unique factors affecting each patient’s outcome, it’s often too complex for a doctor to predict the success of a procedure in any one patient. Thankfully, with the advent of artificial intelligence, computers are ideally suited to this task.

Neural networks for individualized treatment

To better predict laser eye surgery patient outcomes, the authors of this latest study turned to neural networks – computing systems inspired by biological neural systems. These computer systems can learn to perform specific tasks by studying large numbers of relevant examples and identifying patterns that would be difficult or impossible for a human to spot.

“Neural networks are increasingly becoming part of our everyday life, whether they play chess or bridge, expertly translate between languages or predict the movement of the stock market,” says lead research Professor George Anogeianakis. “Ophthalmology has also benefitted from the power of neural networks, and so far, many of the predictions made by such computer systems are as good or better than those from experts.”

Developing a predictive tool

The researchers used data from over 2,000 patients who had undergone laser eye surgery to establish the link between surgery failure and 13 factors that have been reported to influence treatment outcomes. These included five patient-specific factors, such as age and thickness of a layer of the cornea, and eight non-patient factors, such as surgical technique and the temperature and humidity of the surgical suite.

By feeding these data into their neural network, the team found that they could predict the success or failure of a procedure with a high degree of accuracy. “The system is a simple clinical decision tool that identifies patients who are more likely to require a second corrective procedure,” explains Anogeianakis. “The surgeon can simply input the 13 required patient and non-patient parameters into the system before a procedure and the computer can then inform them if the patient is at high risk or not.”

Excitingly, as eight of the parameters – such as the planned surgical procedure – can potentially be modified by the surgeon, it may be possible to adapt surgical plans in response to the computer predictions and thus increase the patient’s chances of a successful procedure.

“It’s a question of medical ethics for doctors to use the most advanced technology to improve their patients’ outcomes and give their patients the most accurate information about their chances of success,” says Anogeianakis. “This system contributes to that goal.”

This "Key Summaries" article is brought to you in collaboration with SciencePOD.

Putting exams to the test: Do entrance exams predict academic achievement?

4open study suggests entrance exam scores may not predict future success at university

Soon, students around the world will begin poring over textbooks for their university entrance exams. Many hope to reach that slim, tail end of the results curve that shows the very best performers. Others may worry about ending up at the other end.

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New research challenges current thinking on cancer

4open special issue presents a new paradigm for cancer

Imagine if we could understand and treat the root causes of cancer, rather than struggling to remove it or mainly treating its symptoms once it has already taken hold. The authors of a new peer-reviewed Special Issue of the open access journal 4open have paved the way for this vision by challenging our understanding of how cancer begins, develops, and spreads.

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Pursuit of profit underlies German nursing shortage

A new study in open-access journal 4open concludes that profit motives and excessive bureaucracy contribute to Germany's nursing crisis

What is the primary role of healthcare – to make profits or care for patients? This question lies at the heart of a new study, “German nursing shortage in hospitals - Homemade by Profititis?” in the open-access journal 4open, which examines the causes and consequences of a nurse shortage in German hospitals. The authors argue that business culture in healthcare has resulted in untenable staff cuts in the name of savings, and a heavy and largely unnecessary paperwork burden for staff.

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Researchers use open-access genetic data to reveal a unique picture of ageing

Using publicly available datasets, researchers have found that genes involved in infections and inflammatory responses are highly expressed with age, suggesting links between infection/inflammation and the ageing process.

What happens to our bodies as we age, and why?

On the face of it, the answers may seem obvious, but the biological mechanisms involved in ageing are not yet completely understood. These questions are more pertinent than ever, as improvements in healthcare mean that the human population is ageing rapidly, but frailty and chronic illness still frequently accompany old age. Uncovering the mysteries of ageing will help researchers to understand the relationship between ageing and disease, paving the way for people to be healthier during their final years.

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