By: Manasa Kalaimalai
Everyday, as situations around the globe worsen and the world grapples with COVID-19, the use of technological innovations has been more incessant than ever as we struggle to find a solution to the crisis at hand. Although we speak of artificial intelligence being the future, it seems as though the future is already here as artificial intelligence and machine learning have the potential to play a significant role in helping researchers and scientists better understand the current pandemic. But how exactly could they be implemented in the current COVID-19 situation? Several approaches are seen below.
Risk Prediction for Covid-19
Machine learning has proven to be an extremely invaluable asset when it comes to risk prediction. In terms of the current pandemic, it is being used in mainly 3 ways :
1. Infection Risk (individual risk of getting COVID-19)
2. Severity Risk (risk of developing severe complication of COVID-19)
3. Outcome Risk (risk for treatment to be ineffective and risk of death)
In order to do the above, researchers are developing a multi-source deep neural network-based predictive tool to combine demographics policies, regional infections, and individual risk information for accurate risk evaluation.
Diagnosis of COVID-19
Testing patients on a large scale not poses challenges regarding safety, but is also very costly, especially in the earlier stages. Considering that the symptoms of COVID-19 are quite common- cold, cough, sore throat- many patients are bound to be concerned that they might have contracted the disease if they come across any of the symptoms. This causes testing processes to become much slower and costlier. This is where machine learning comes in to simplify, quicken, and make the tests cheaper.
Upon entering a hospital, patients in a Florida hospital were to undergo a face scan that uses machine learning to detect whether or not they have a fever. Doing so helped aid nurses triage between patients effectively.
Furthermore, many doctors nowadays are dealing with 20-hour work shifts with an influx of patients every continual day. A significant amount of their time is spent answering the basic questions of distraught patients, whereas they could be focusing on patients facing more dire circumstances. In this case, chatbots- acting as self-triage systems- could be implemented wherein people self-identify the best course of action to take based on their given symptoms. Large companies, such as Microsoft, have already begun releasing these chatbots for public use.
Deep learning techniques under machine learning can prove to be extremely indispensable considering how critical it is to develop a vaccine as soon as possible. Although current methods involve a tedious and long process of trial and error, machine learning could speed up this process significantly using supervised learning methods to narrow down on several potential drug compounds that have potential to be a vaccine. An investigation regarding the same idea was conducted by Benevolent AI, a UK AI company, where within days they found that Baricitinab ( a drug used for rheumatoid arthritis) proved to be the most prospective candidate for a vaccine. Baricitinab is currently in late-stage critical trials.
Clearly, machine learning has the potential to solve the global pandemic that billions are struggling to push through. It is truly amazing how quickly organizations are implementing machine learning methods to address COVID-19 and aim to bring to fruition the promises that technological innovations in artificial intelligence were to fulfill for future crises. Now only time can tell whether or not machine learning will truly be able to successfully solve in the current calamity we’re facing or whether its promising applications are just overhyped.
Written by: Michelle Hashem
Mental health research has skyrocketed in the past fifty years. We have gained so much more of an understanding of illnesses like depression, anxiety, and ADHD. Although this has allowed us to better recognize different disorders, it has also opened up a wider market for the development of drugs--and the abuse of them.
Adderall and Ritalin are two major medications used to treat ADHD. Adderall basically strengthens the effect of neurotransmitters like dopamine, which helps with memory and attention, and norepinephrine, which lowers hyperactivity. Ritalin can increase attention span and decrease hyperactivity and impulsiveness.
According to the CDC, 62% of children with ADHD are medicated. They are advertising literal amphetamines to children. Think about how these kids are potentially forming a dependence early on to these medications that are widely known to be addictive. Not to mention the other affects it can have on their health in the long run. According to the American Addiction Center, the long term effects of taking amphetamines like adderall can be irritability, depression, and even heart disease. When I learned that doctors are recommending such serious medications to such a large number of kids suffering from the disorder, it hit me that drug companies don’t only care about helping people with mental health issues.
According to a study I found that was well explained by Health Affairs, global spending on drugs like adderall and ritalin increased by about 17.6% a year from 1993-2000, and after that, it jumped to a 40.9% increase in spending a year and has been growing since. That is crazy! Drug companies must be making big money off of that.
On top of the fact that people all over the world have been going crazy over these medications, this article concluded that “This study has confirmed that the United States is by far the world’s largest consumer of ADHD medications. Why other countries have lagged behind is not well understood.”
To put it in perspective how dependent the US is on these drugs, the number of prescriptions for stimulants for disorders similar to and including ADHD in the US was 5 million in 1991. In 2007, it was 35 million and is still climbing today. Something that is also important to take into account with any drug is the amount of people abusing them. This is especially the case with ADHD medications. Since 1995, ritalin, or methylphenidate, has been ranked the top most stolen drug by the Drug Enforcement Administration.
And abuse is on the rise--according to Johns Hopkins University, from 2006-2011, abuse of adderall had gone up 67%, and emergency visits up 156%. It is obvious we have a drug crisis in this country, but ADHD medications like adderall and ritalin are often overlooked. Professor Ramin Mojtabai “suggests that drugs like Adderall should be treated with the same scrutiny as prescription painkillers.”
It might be a good thing that more people’s ADHD are being diagnosed and treated, but to every accomplishment, there is a dark side. It depends on whether you are willing to ignore it or not.
The Psychology of Bias
Written by: Sarah Frank
Imagine that you are a girl walking down the street alone at night, and you see a man in a hoodie start running in your direction. Odds are that he is just a guy jogging on your street… so why would this likely make you nervous?
Allow me to introduce you to the concept of an alief. Aliefs are subconscious belief-like states or ways of thinking that influence our actions and behaviors. Aliefs were first introduced by Tamar Gendler in her paper “Alief and Belief.” An interesting thing to note is that you don’t even have to really believe it’s true for the alief to affect your actions.
Aliefs, as Tamar Gendler describes them, are “associative, automatic, and arrational”. They have three major associated components: they involve the representation of an object/concept, they involve experiencing an emotional state, and they frequently lead to actions (motor routines, as she calls them).
Gendler provides the example of a Skywalk where you walk out onto glass high up. The adrenaline rush and the souvenirs with the words “I did it” tell you that it was a brave or bold thing to do. As Gendler argues, though, you wouldn’t have stepped onto the Skywalk if you thought there was any danger.
On one hand, you must believe it’s safe to step onto the Skywalk or you wouldn’t have considered it. The hesitation and fear you might feel, though, is caused by your alief— even if you know it’s not the case.
In this scenario and in other scenarios, there is an implicit and automatic alief that goes against what you actually believe. This can result in a belief-behavior mismatch, the term for when one’s behaviors contradict what one believes. Many people pride themselves on acting based on their values and beliefs but that’s not always the case. An alief can influence these actions.
Take, for instance, Paul Rozin’s experiment. In the experiment, participants pour sugar into two vials, one of which was previously labeled as holding poison but is obviously clean. The participants then pour the sugar from the vials into glasses and choose one to add water to and drink from. They almost always picked the cup with sugar from the unlabeled vial. Rozin’s experiments showed that people have biases that they know aren’t the case but are still impacted by.
Another example of an alief would be if you know your phone is in your pocket but reach to check anyway. You believe it’s there but an alief tells you to check, even though you know there’s no real reason to be worried.
This is also an example of a belief-discordant alief: an alief that complicates a pre-existing thought or opinion. On the show Brain Games, people were presented with two different types of brownies. One set of brownies was shaped normally but had a mediocre recipe. The other set was advertised as deluxe and fudgy but was shaped like dog poop. Most people chose the first set even though they knew the second ones were still just brownies.
Aliefs are present in everyday life: things you know aren’t true but act on anyway. Noticing the difference between aliefs and beliefs, between the true and untrue, is the first step to understanding your own actions. Beyond your own actions, though, keeping aliefs in mind can help you understand other people’s actions, especially in a day and age where implicit bias is more rampant than ever.
By: Maria Rizwan
Wouldn’t it be incredible to foresee what you transpire to be? With a single segment of your DNA, its most certainly possible. We have all heard about cloning, biohacking and genetic engineering but ever have you pondered upon the science behind it? A DNA strand is the most complex yet intriguing part of your system. It encompasses the key to life and modification. A genome is the sum total of an organism’s DNA which carries one’s entire genetic history and information. A biological chest full of myriad of treasures of information, rendering potential for breakthrough discoveries, but to acclaim the gold, one must cover the journey of genome sequencing.
Whole genome sequencing is presumably the course of uncovering the complete DNA sequence of an organism's genome at a single time. This sequencing process can be fathomed to be a semi-decoding route. Decoding the genome sequence, aids the comprehension of it, however a human genome is quite multifarious. Reckon the genome as a book lacking structure and legibility, merely adorned with nonsensical strands of letters. Similarly, the nitrogenous bases in our DNA, denoted by the letters: A, T, C, and G deem to be arduous with their infinite number of combinations.
This was all done manually in the past. Hours of identifying the convoluted sequence was quite draining. To find the concurrent genome and to stitch it to form a meaningful sequence, all whilst ensuring it’s investigated on the organism’s chromosomal DNA that is present in the mitochondria, was no easy task. The first successful sequence credits back to 1998, a Caenorhabditis Elegans, widely known as a Nematode worm, a precedent for the forthcoming pioneers. Soon after, a full genome sequencing was executed on a female from Netherlands.
The impressive part of genome sequencing is that, one needn’t to extract a full body sample of DNA. Almost any biological sample with slight traces of or ancient DNA, itself, can provide full access to the organism’s genetic ancestry. Samples like saliva droplets, epithelial cells, and hair strands can print out the required data.
Over the years, distinctive methods of genome sequencing came to exist. The Nematode worm was examined and sequenced utilizing a ‘whole genome shotgun’, involving the breaking of genomes to minute pieces, and reassembled into a sensible genome sequence. Another strategy scientists use is the ‘clone by clone’. Contrarily where the genome is butchered into sizable, rather than minute, pieces, and then mapped out to figure where in the genome the clone belongs to. Lastly, the mapped clones are cut into further pieces and overlapped to construct a complete genome sequence.
The discovery of genome sequencing has endowed a valuable shortcut to the medical realm, enabling scientists to locate genes more effortlessly and efficiently. Once a genome sequence is complete, further analysis conducted discloses the sequence’s functions in terms of growth, reproduction, and maintenance of the whole organism.
Dr. Jason Vassy, a medical specialist from Boston, put this theory to test in attempt to discover rare diseases on his sample size of 50 patients. In hope of discovering one such diseases, Vassy unearthed 11 rare monogenic ones. Furthermore, to his surprise, none of the patients exhibited any symptoms of their presumed genetic disease. The study additionally consolidated data about possible gene mutations and the necessitated patient care accordingly.
Analogous tests and studies are being conducted today relevant to the SARS-CoV-2 pandemic, COVID-19. Immeasurable global efforts see to synthesize over billions of DNA samples. Probing through this genetic sequence will grant the scientists an idea of COVID-19’s mutating nature. Doctors trust DNA analyses can reveal the genetic mutations and variations of the virus, the catch to the pending cure. India and UAE both have ramped up their tests to collate as much as data as possible. Contemporary reports suggest that the virus has over 40 strains and 70 mutations, which awaits the sequencing process. Moreover, UAE concluded its premiering whole genome sequencing project on the 15th of May and profitably reported the genome to entail 30,000 genetic bases. Currently, the aim is to expand the testing and completely sequence the 240 samples they have in place. Researchers and scientists are working turbulently all around the world in attempts to flatten the curve and hopefully restore us fruitful health.