There are multiple tracks with different subthemes. It is not required to join a specific subtheme, but the advantage of joining some subthemes (indicated with xxx supported) is that you get to work directly with an experienced team. Please reach out to the helpers in the discord channel to be connected with these teams. If you do not want to join a specific subtheme, just go immediately to the General Track Description section per track. 

Please use this table of contents to find the track or subtheme of your liking: 

  • Informational and Coping Tools
    • General Track Description
    • Subtheme: AskCo19 (Nth Opinion supported)
    • Subtheme: Epidemic/Social Modeling (SingularityNET supported) 
    • Subtheme: Fake News Detector (SingularityNET Supported) 
  • Medicine and Epidemiology 
    • General Track Description
    • Subtheme: Biomedical hypothesis generation using OpenCog Bio-AI (SingularityNET supported)
    • Subtheme: Personalized Prognosis Models (SingularityNET supported)
    • Subtheme: Coronavirus and Longevity Research (SingularityNET and Rejuve supported)
    • Subtheme: Machine learning for CT scan diagnosis (SingularityNET Supported)
  • Privacy and Sovereignty 
    • General Track Description
    • Subtheme: Trustless Epidemic Tracking App (SingularityNET supported)
  • Open Innovation
    • General Track Description
    • Subtheme: Supply Chain Innovation

 

Informational and Coping Tools - General Track Description

Covid-19 has led to huge changes in the way people live, what tools can be developed to ease the effects of this?

The Challenge

A key factor in slowing down the spread of Covid-19 is our ability to test for Covid-19 and trace all of the potential contacts a person may have unwittingly infected.  We are looking for participants that can help build tools that will allow everyone to be better informed and help cope with the extremities that may arise during a situation like COVID-19 lockdowns, economic impact, and loss and, thereby, reduce social isolation

 

Context

  • The psychological effects of the unknown can be devastating, and under lockdown, conditions could easily lead to depression and even suicide. The ability to make decisions may also be impaired which could be critical in a crisis situation. 
  • Helping people assess the validity of information and identify likely fake news.
  • The economics of dealing with global crisis situations such as pandemics depend on so many variables that it is difficult to plan for, which in turn leads to poor supply provisions to cope with such events.

Impact

  • Better informed citizens lead to shorter personal and economic impact, reducing damage to the economy and stress levels. 
  • The stress on the healthcare system may have long-lasting effects. For example, those in need of treatment may be getting a postponed treatment. Figuring out ways to cope with this is essential for mental health. 
  • 28% of all US households are single-person households. During lockdown periods they all would be in a type of solitary confinement. Some may not even have contact with others on the phone. 15 days of solitary confinement can already lead to permanent psychological damage. 



A successful team will

  • Create a prototype that demonstrates:

    • A path to reduce social isolation
    • Label public places as low risk or high risk for contracting COVID-19 
    • Identify places where PPE may be needed to protect the individual

 

Informational and Coping Tools - AskCo19

The Decentralized AI Alliance, under leadership of SingularityNET and Ocean Protocol, has launched a major developer event to extinguish the threat of the COVID-19 pandemic and end social isolation using a state-of-the-art full stack AI solution that their team has developed on a decentralized protocol.  Hosted by DAIA, SingularityNET, Ocean Protocol and NthOpinion are teaming up to launch a global hackathon, named CoVIDathon, online with multiple tracks for developers to participate. In this proposal, NthOpinion has outlined a theme for the Informational and Coping Tools track which will feature the development of a distributed AI interface for frontline providers utilizing televideo, tokenomics, and machine learning in a simple interface for frontline providers to share awareness about Covid-19 and personal experience and foresight for people yet to face the virus in real-time. 

 

The Challenge

  • Create an interface whereby a frontline physician can interact with his own AI: Incorporate algorithms formally trained to be utilized for  (physician trained and owned algorithms)
  • Implement the NTO ERC20 token as an “opinion” token for punishment/reward in a  reinforcement learning system

 

Join our Github

 

Join our Slack

 

Context

    • Nth Opinion open sourced a project originally envisioned to be an AI Physician platform that would be decentralized and borderless to help people answer their concerns about their conditions and diseases 24 hours of the day without the need for a physician. 
    • In the emergence of a lethal and unknown viral pathogen, SARS-COV-2, Nth Opinion saw the advantage of its system to give people around the world advanced warning by frontline physicians to begin to prepare for the oncoming surge and onslaught of the pandemic of COVID-19.  The spread of the virus rapidly outstripped the resources of one company and that was when their team turned to the open source community as a call to action. With SARS-COV-2 spreading at a frightening pace, the open source community answered the call and fought back with amazing clarity and force.  Members of the open source community, each with their unique talents, applied their skills to challenge this global threat in our hackathon event, Code vs COVID-19 and produced a platform that the community has called AskCo19.com. 
    • Without a cure or any research, the advance warning of people and physicians on the frontlines with their awareness, personal experiences, and suggestions become the only advantage that people, yet to face the surge and onslaught of COVID-19 in the midst of the pandemic, can use against a lethal and unknown viral pathogen. 
    • The QnA style design is intentionally done to produce a natural UI/UX that will facilitate a physician-patient experience that can be scaled to an application for patients around the clock. The structure lends itself extremely well to creating a high quality simple NLP dataset that AI/ML and Reinforcement Learning can use to create a reward structure to enable training and the introduction of a trainable action space that will optimize answers to questions about treatment options, experiences, and advices which could improve over each iteration/epoch.  
    • In real-time, users become the environment and the RL agent optimizes over every decision as steps.  
    • The agent works in shadow-mode, coined by Tesla, until its accuracy exceeds the threshold that will be acceptable clinically.  
    • To promote engagement, we are encouraging the use of a utility token to incentivize the physician and patient experiences either separately or during their encounters. Tokens may be used, earned, or burned based on participation.
    • To facilitate dataset growth, we will enable telemedicine as a way to create engagement and promote the use of the platform for which questions can be asked during the patient-physician encounters that are not answered or still need answering. 

Impact

    • COVID-19 has shut down clinics around the world and, without access, patients no longer have access to their medical providers.  AskCO19 immediately fulfils this need during the time when a pandemic has crippled the system that was intended to help the patients that are most affected by it. 
    • Until now, health care systems have been falling far behind in technological advancements leading to widespread inefficiencies in communications with and between healthcare workers and patients. As a result, it has become ill-equipped to handle emerging infectious diseases, particularly COVID-19 with pandemic effects. This has resulted in desperate efforts to advance its technologies and policies. Nth Opinion has been ahead of the curve and has developed a full stack solution for physicians two years in advance. 
    • Deployed and open sourced weeks before the pandemic, AskCo19 now is the main platform for over 200 developers to unite against a biological agent that threatens our existence and will not wait for us to stop it. 
    • The only advantage that people have is the advance warning from people for people. A virus that spreads with an Ro of 2-3 is exponential and, in our globally-connected world, has no borders.  As a technological species, humanity will decide its fate with our advances in global communication, decentralized technologies, self-adaptable, self-learning, and potentially superhuman algorithms. 
    • Once decentralized, it will continue to gather knowledge and improve treating and finding new solutions for new diseases as they emerge in a borderless and permissionless way. 

A successful team will

    • Work well with the open source community to rapidly advance features with laser sharp focus to extinguish COVID-19 and advance the AI/ML and RL physician algorithm
    • Port features that are well-suited onto SingularityNET’s decentralized protocol
    • The development of the first AI Solution that will become aware of and self adapt to threats from any emerging infectious disease to be able to significantly cripple a fast-moving, self-adapting, and highly dangerous infectious biological pathogen as it emerges and prevents pandemics. 
    • Deploy blockchain technology through the use of a smart contract / utility token
    • Be the proof of concept that a decentralized AI solution can not only monitor for the emergence of rapidly spreading, dangerous infectious diseases, but can also be the solution to extinguish them before significant mortality and morbidity occurs with implications for a borderless and permissionless solution to protect every person in the world.    

 

Informational and Coping Tools - Epidemic/Social modeling based on publicly available data 

Current simulations are overly simplistic. They can and must be extended in a number of ways. Crucially, they need to model intervention effects.  The best way to do this is via implementing more sophisticated micro-level simulations -- i.e. agents-based modeling, which has been used to excellent effect in other contexts. 

 

First, combining better agent-level simulations with intervention modeling should lead to more accurate predictions about contagion, hospitalization needs, ICU needs and death rates.

 

Second, better agent-level modeling lets one more accurately simulate both the medical and economic impact of varying degrees of lockdown. 

 

Third, a more accurate simulation that lets users configure agent behavior to match their lifestyle (someone who drives to work in a small office vs someone who takes the subway to a customer-facing job in a large mall have very different exposure profiles) can be educational for the general population, and can be used to cement the need for confinement and lockdown in critical areas. 

 

Finally, this can be integrated with the healthcare system and the tracking app [see above] to show close to realtime risks based on the current situation in the user's location, which quarantined people can use to guide their decision making based on their risk level (order food, go to a grocer during off hours, go to a drive-in in a lower risk area).

 

 

Medicine and Epidemiology - General Track Description

Assistive medical and research tools that can help us understand, diagnose, or treat Covid-19 better

 

The Challenge

Covid-19 has a relatively simple RNA structure, but has brought the world to a standstill, and it could take at least 1-2 years before we have an effective vaccine. We are looking for participants that can help build tools that will use bioinformatics to learn more about the coronavirus, its potential mutations, and long term effects. Moreover, we are also looking for submissions that help to accelerate drug discovery or speed up the creation of potential vaccines, and that help frontline healthcare workers diagnose Covid-19. Furthermore, tools that can assist in diagnosing Covid-19 (or rank likelihood of Covid-19 compared to e.g. flu or common cold) by means of AI will support triage and logistics, contributing to a relief in resources of response teams.

 

Context

    • Healthcare facilities fighting Covid-19 are underequipped, understaffed, and ill-prepared to treat the wave of cases globally. Further clinics have been shutting down.  There is further limited access to healthcare providers.
    • Normal diagnostic procedures are being overrun by the sheer number of cases needing to be diagnosed lengthening the time it takes to treat patients.
    • There is a lack of hospital beds and intensive care resources to handle COVID-19. The RNA test swabs currently take 3-5 days before results return.  Without a rapid diagnosis, resources are spread thin. Imaging, vitals and labs are not specific enough independently to make a diagnosis of COVID-19. A tool that can rapidly risk stratify patients as high risk and low risk would greatly reduce wait times for COVID-19 testing and allow hospitals to give better access to their patients. 
    • Labs that have been implicated that have features significant for COVID-19 disease include serological tests such as markedly elevated levels Ddimer, CRP, and Troponin as well, leukopenia, reduced levels of white blood cell counts. Lab testing and early risk stratification can be done with many of the serological tests to increase the sensitivity, specificity, precision, accuracy, as well as negative predictive values while the patient is returned home either for testing or not.  This system can act as a way to further improve and reduce the false negative from the gross screening protocol for countries that are not testing very vigorously. 
    • Treatment proposal: The infection, SARS-COV-2, has two phases in the course of its infection, the viremia and the inflammatory phases.  Currently, the most significant and most critical phase that has caught frontline workers off-guard is the inflammatory phase. Based on testimony from the editor and chief of the European Journal of Heart Failure, the inflammation does not respond to any known treatment. As a priority, it has been recommended to prioritize finding a treatment solution. 
    • Discharge of COVID-19 patients: a big challenge that is yet to be realized is what to do with the large number of recovering COVID-19 patients.  Rehabilitation centers, physical therapy centers, and skilled nursing facilities as well as nursing homes are under-resourced to care for returning or recovering COVID-19 patients.  The homeless populations or patients that are returning to shelters are going back into the community and is yet to be determined whether we have the appropriate screen techniques to release these patients back to the community.  A strategy of testing and monitoring will be necessary for these patients.  


Impact

    • Rapid testing and risk stratification
    • The ability to take demographics data, serological results and provide real time diagnosis for patients with COVID-19
    • Home testing using currently routine serological tests would greatly reduce the need for scarce COVID-19 testing resources and decentralize the testing for COVID-19 from centralized healthcare control.  Social impact will positively be affected with a larger population of negative COVID-19 results. A high risk COVID-19 detection would prompt urgent self quarantine and contact tracing and would provide a significant defense against COVID-19 resurgence in the community and cluster detection.   
    • Treatment of the inflammatory phase will greatly reduce morbidity and mortality of the COVID-19 disease and markedly reduce the need for scarce intensive care resources making the treatment of COVID-19 far more manageable as a vaccine is still to be realized. 
    • The discharge of COVID-19 patients will be challenging for the return back to the ill-equipped community for the morbidity that these patients have. The testing and monitoring of these patients will be essential for ongoing management for the populations.    




A successful team will


    • Building new testing and risk stratification methods
    • Build a system for resource allocation from the community for COVID-19 patients that are transitioning back to the community after discharge.
    • Testing and monitoring of patients ready for discharge
    • Visualization of the virus in real-time in the environment.

 

Medicine and Epidemiology - Biomedical hypothesis generation using OpenCog Bio-AI (SingularityNET supported)

Apply our natural language processing pipelines to the publicly available corpus of coronavirus publications, and feed the results into the bio-atomspace, which integrates a large number of curated background knowledge resources. Extend the bio-atomspace with more specialized resources. Apply probabilistic reasoning techniques to rank multiple existing suggestions entered by human experts based on the entirety of the knowledge ingested. More speculatively, apply probabilistic reasoning techniques to automatically generate hypotheses for possible treatments as suggestions for wet lab work.

 

Medicine and Epidemiology - Personalized Prognosis Models (SingularityNET supported) 

Prediction, for a patient suspected or infected with coronavirus, of whether their infection is going to be severe or not.  This could be based on any available data including genome sequence, gene expression data, clinical markers of various sorts, etc.  Any data indicating lung health would be critical here. This would be of significant practical value in terms of recommending courses of treatment for patients, guiding who needs to be hospitalized when, who should be taking which preventatives, etc.

Medicine and Epidemiology - Coronavirus and Longevity Research (SingularityNET and Rejuve supported)

The jump in severity of cases of Coronavirus over the age of 60 suggests a possible involvement of the midlife switch, a biological phenomenon currently under study by the SingularityNET ecosystem bio-AI team.  The midlife switch (a change in gene expression patterns occurring around age 60) has been shown to inhibit Mtor pathways that produce IFITM proteins which resist IFITM sensitive viruses including Influenza A, MERS Coronavirus and possibly COVID-19.  It has also been shown that the midlife switch promotes autophagy, which in turn promotes some virus infections such as Influenza A. However, both autophagy and Mtor inhibition promote longevity.  

 

We will take a look at the data of viral infections and longevity, including chloroquine, a autophagy inhibitor and its possible effects on COVID-19, as well as differential expression of autophagy pathways between the young and the old, and with our Neural-symbolic knowledge graph and multimodal data embedding space.   This inference engine can consider data from multiple sources simultaneously, including raw data, data from clinical trials, ontological biological genetic data. We have established a method to focus the lens on what is salient in unbalanced data as well as to guide inference.

 

Medicine and Epidemiology - Machine Learning for CT Scan Diagnosis (SingularityNET supported) 

There is an open access COVID-19 CT scan dataset, which can and will soon be used for machine learning diagnostic models:

https://www.trainingdata.io/blog/covid-19-dataset-annotation-collaboration/ 

Multiple groups will probably soon have good models on this data, but one should go beyond that. To create a system that can also work in the future and help with future pandemics would require a constant sharing of CT scans by hospitals to then automatically detect anomalies. If the data can be shared anonymously and the patient remains in control of their data (they can remove it and only give certain parties access to it), then this would be a worldwide scalable system that could also improve reaction speed for future pandemics.  

There are no technological obstacles to achieving this, just cross-organizational logistics and regulatory gymnastics.

 

 

Privacy and Sovereignty - General Track Description

Developing censorship-resistant tools to communicate during crisis situations and ensuring open access for all to essential information shared by subject matter experts.

The Challenge

Data is all-important when attempting to solve a problem, the more data the more accurate a solution can be developed, though obtaining data can be difficult while protecting the rights of individuals. Therefore, we are looking for participants that can help build tools that will allow subject matter experts to communicate freely during crisis situations with each other and the public. 

 

Context

  • Doctors in China had information but were unable to share information in an easy way with others. 
  • Those that did often got into trouble. Some were persecuted for it or arrested. 
  • Doctor Li Wenliang, a coronavirus whistleblower died of coronavirus later. Let us not forget his story.

Impact

  • Providing a safe way for subject matter experts to share information with each other and the public. 
  • Encourage sharing of information between physicians globally, being ahead of the curve by learning from others. 

 

A successful team will

  • Create a prototype that demonstrates:
    • Verify who the experts are and who are not. 
    • Communication between experts whilst guarding anonymity.
    • Communication with the public in an effective way.

 

Privacy and Sovereignty - Trustless Epidemic Tracking App (SingularityNET supported) 

Successful epidemic containment strategy in some countries has relied on tracking individuals through cell phone location history. This is useful yet leads to privacy concerns. A trustless decentralized approach can ensure the relevant data is securely stored and used exclusively for epidemic containment reasons. This would take a form of a dedicated app, which can be expanded to collect clinical data from wearables, questionnaires and self-reports. Users can also volunteer contact information for others they've been in close proximity with, allowing tracing of the "tree of contagion" and automating the outreach effort by healthcare services. 

 

Wearable data can be used for early illness detection -- this is a straightforward ML application exploring subtle deviations detectable by wearable devices.  Early detection is critical for both containment and mitigation, and can be used to prioritize patient testing while diagnostics are in short supply. A more speculative application is differentiating between COVID-19 and regular influenza or cold.

Open Innovation - General Track Description

Creative thinking is key to our eventual success against Covid-19, this track is for contributions that don’t fit into the other tracks.

 

The Challenge

This Pandemic unfolded at breakneck speed and seemingly took the world by surprise even though the tremendous risks to the world of such an event were very well known. Bill Gates was among many high profile people warning countries to prepare. If the world had listened at that time, what should, or could we have changed then to protect us now, and what can we do now to protect those in our future? A large degree of open thought is needed here to come up with solutions no others may have thought of

Context

    • Covid-19 started with a single transmission from animal to human, and spread around the world in a matter of weeks due to our international way of life
    • The success of Covid-19 to spread wide and far has much to do with the fact that many infected people are simply unaware they were infected.
    • Health care systems have been overrun by the number of patients
    • Vital PPE and ventilators have been in short supply leading to companies repurposing their manufacturing processes toward this end, and 3D printers being leveraged like never before. 
    • International communication systems have been leveraged to pass along freshly learned information so that what was learned in one place could lead to coping strategies being implemented in another.
    • Global supply chains have been utterly stretched leaving many people without basic supplied

 

Impact

    • Reduce the overall spreadability of diseases like Covid-19
    • Find ways to help healthcare systems cope better under stress conditions
    • Help supply chains achieve better preparedness and reaction 
    • Asses risks of novel viruses occurring and mutation
    • Any other possible solution to deal with any other need that may arise from a global pandemic or other global crisis. 



A successful team will

  • Build a tool that provides a new perspective or approach to an existing problem during the COVID-19 crisis. 
  • Demonstrate how this would be able to help and be implementable

 

Open Innovation - Supply Chain Innovation

Covid-19’s rapid emergence left healthcare workers and communities woefully unprepared to handle the challenges they now face. Creative solutions are now needed to create and allocate resources where they are needed the most. The challenge is to provide the resources at the locaitly of need, given containment of the disease is the key, moving patients to locations of availability of resources would be a challenge

 

The Challenge

Across the world healthcare workers on the frontline have a dire shortage of the protective gear they need to treat patients safely. In the absence of real protective gear there have been reports of nurses wearing trash bags and relying on 3d printed parts for eye protection. There is a pressing and unprecedented need for ventilators as well, and in the absence of more these vital resources will need to be rationed.  Outside of hospitals there are imbalances in supplies like hand sanitizer and food, with some people unable to get basic resources at all.

Context

  • Hospital systems have implemented rationing of PPE and, even though, SARS-COV-2 is a aerosolized pathogen, workers are at risk with limited to no PPE or masks
  • People are taking an unnecessary risk coming to work without proper protection due to atmosphere that is foster poor safety practices. 
  • Supplies or protective equipment and ventilators are not reaching the frontlines due to inadequate information at where these resources are and how to get them