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AI: Advancing Medical Facilities and in Diagnosing Diseases

The advent of AI in diagnosing diseases and innovation has brought a robust improvement in the field of medical science. While there are multiple attempts to increase life expectancy around the world and find solutions to critical illnesses, the healthcare industry continues to face challenges. The growing demand for the services catalyses the need for a robust system and a strong workforce that can meet the needs of the patients. Well, there is a need to understand that increasing healthcare spending is not the ultimate solution unless there is structural change.  

AI: Revolutionising Healthcare and in Diagnosing Diseases

This can be eliminated with Artificial intelligence which has the potential to revolutionise the healthcare industry as it is aimed at providing better care and improving the day-to-day life of healthcare practitioners. After decades of following the same pattern, the healthcare industry needs to adopt a more dynamic approach. A minor delay in diagnosing the disease can pose a risk to the entire population.  

You may recall how thousands of people died every day due to the COVID-19 pandemic when there were no signs of the vaccine. Talking about the branch of Artificial Intelligence, it has implementation across multiple industries, and medical healthcare is no exception. AI can provide automated human support and increase the efficiency of the diagnostic process. Can AI also help with the correct diagnosis or the development of new treatments? Let us ascertain how AI is improving the growth patterns of the healthcare industry.  

AI in Diagnosing Diseases at an Early Stage  

Consider how a doctor would have to gather each report and look one by one to gain an understanding of the disease and the direction in which it is progressing. Although machines can never surpass analysis done by a human, but they can definitely ease the process.For instance, an AI-based health app can also help keep track of factors such as pulse rate, heartbeat, and other necessary details. It may turn out to be beneficial for both the patients and the doctors. While it can be easier for a patient to judge when they should seek their next appointment, healthcare professionals can leverage it to study any patient’s case.  

Correct diagnosis of the disease can take years of medical training. In comparison, machines can provide or draw conclusions even in a fraction of a second. The only condition is that the entire set of data will have to be digitised. The algorithms cannot read between the lines but can keep track of all the patterns similar to healthcare providers. AI in diagnosing diseases improves the chances of detection of diseases at an early stage.  

Revolutionising Drug Discovery  

Well, you cannot deny that human bodies are complex. At times, it may take a few months to detect a new medicine to treat the disease. In other cases, it may even take years to discover the impact of medicine to successfully treat a disease. In previous times, scientists would spend a lot of time conducting manual testing. However, times have changed, and it has become easier with the help of AI. With the data and information available in one place, hypotheses can be developed. AI can provide a quicker validation of the drug target and how it will perform. The records can even help study how the drug has reacted in the past and carries the tendency to impact in the future.   

All these aspects can be analysed and aided to develop new treatments for diseases. AI is well-trained to predict drug efficacy and side effects, which can be highly beneficial for scientists. The professionals may even be required to perform advanced math on large volumes of data. This can be accessed easily with the help of Artificial Intelligence. Leveraging data to make faster decisions can help discover the full potential of medical professionals.  

It can help them identify new targets for intervention and how a compound will react with a target molecule. It can also help predict suitability and identify the ideal biomarkers. 

Summing Up  

We can say without any reluctance that AI can automate a large amount of manual work. It helps speed up the process and even assists in personalising the treatment according to the condition of an individual. However, it is just the beginning. Unifying the medical data and digitising everything can help find valuable patterns in which AI in diagnosing diseases can help make accurate and cost-effective decisions. 

AI Conversational AI

ML Enhancing Cyber Security in Conversational AI’s

We all know how advanced the web has become. But, along with positive advancement, there has been some negative modernization in the cyber world. Hacking, cyber attacks, and phishing to name a few by ML are enhancing cyber security.

Do you know? Nearly 236.1 million ransomware attacks were reported globally only in the first half of 2022!  

This makes cyber attacks a concern to address immediately. Cyber-attacks are a widespread issue in today’s society for both people and companies. These assaults can potentially cause sizable losses in terms of money, confidential information, and brand image for businesses. Though traditional security systems are used as security in the beginning, these can no longer keep up with the continually changing dangers due to increasingly sophisticated cyber threats.  

Machine Learning then emerges as one of the best alternatives. ML has consequently become prominent in the defense sector over the past few years. But, what is it?  

What is Machine Learning? 

A subfield of artificial intelligence known as “machine learning” uses statistical models and algorithms to help systems learn from their past performance without being expressly coded. To find patterns and trends that can be used to make forecasts or choices, a lot of data must be analyzed!  

ML makes data analysis, and interpretation way faster and more accurate! But, how can it help manage cyber attacks?  

Role of Machine Learning in Cybersecurity 

Machine learning can assist in various steps of cybersecurity. Threat identification, vulnerability management, and crisis reaction are some. Let’s discuss how-  

Threat Detection 

It can be said that if a threat is detected at the right time, cyber attacks can be saved. Machine learning algorithms can analyze vast quantities of data to find trends and abnormalities that might point to a cyberattack.  

These systems can be very effective at spotting and preventing attacks because ML algorithms can learn from earlier breaches and adapt to new ones. This can significantly increase the chance of threat detection. Further, anomaly detection, behavior analysis, and predictive analytics are some of the frequently used approaches in machine learning-based danger detection!  

Vulnerability Management 

IT system flaws in an organization must be identified and fixed in order to prevent hackers from exploiting them. Though many technology principles struggle to do this, Machine learning can be used to examine network activity, software configurations, and other data sources to look for potential security vulnerabilities. This information can then be used to prioritize fixes and updates to lessen the risk of an attack. Thereby, allowing organizations to manage the vulnerability of their servers.  

Incident Response 

Think of a scenario when your servers have been hacked. Or compromised? What will you do?  

Machine learning not only helps in pre-phase but also allows management once the attack has happened. To begin with, a cyberattack’s scale and severity can be determined using machine learning, and the best course of action for retaliation can be recommended. This may entail putting additional security measures in place to guard against assaults in the future, stopping malicious traffic, and isolating compromised systems. 

We have discussed how machine learning can assist in managing cyber attacks and achieving security over the web. But, would it be beneficial for you? Is this the wise decision to leverage machine learning to mitigate cyber-attacks?  

Benefits of Using Machine Learning in Cybersecurity 

Using machine learning in defense against cyberattacks has a number of benefits. From pre to during and after the attack, it can benefit on various levels.  


Machine learning methods’ large-scale, real-time data analysis allows quick threat detection and mitigation. This lightens the burden on security teams and frees them up to concentrate on more important duties!  

  • Enhanced Accuracy 

Traditional security systems may overlook patterns and anomalies that machine learning algorithms can spot. This can significantly improve the precision of danger identification and avoidance. 

  • Scalability 

Machine learning algorithms are perfect for companies with extensive and complicated IT systems. This is because they scale readily to handle large amounts of data. that too without any hefty or lengthy process or updations!  

  • Adaptability 

Machine learning algorithms are extremely effective at recognizing and thwarting changing threats because they can learn from previous assaults and adjust to new ones. This makes these systems fit for the new world!  

All these advantages of using machine learning do not come easily. And, often challenges arise!  

Challenges of Using Machine Learning (ML) in enhancing Cyber security 

Data Reliability  

Machine Learning algorithms function based on data. To be useful and solve the purpose, machine learning systems need high-quality data. This can create a loophole in the utility of ML algorithms in cyber attack security! The efficacy of the security system can be harmed by incorrect forecasts and false alarms caused by low-quality data.  


Because machine learning algorithms can be highly complicated, it can be challenging to understand how they make decisions. And, a fault or incomplete understanding can have consequences. This can make it difficult for security teams to comprehend the rationale behind a particular choice, making it more difficult to fix possible flaws.  


Artificial intelligence (AI) overuse can cause complacency and a false sense of security. Organizations must ensure that machine learning is used to supplement human decision-making rather than replace it. 

Best Practices for Implementing Machine Learning (ML) enhancing Cyber security. 

It is believed that the maximum potential of machine learning can be surfaced only if it is implemented correctly. Following best practices then becomes important.  

  • Set Clearly Visible Goals 

It is crucial to establish distinct goals and aims before implementing machine learning-based cybersecurity. Therefore, before moving ahead with actual integration, ensure you set clear goals!  

  • Utilize Reliable Data 

To be successful, machine learning systems need high-quality data. Ensure the system’s information is correct, current, and error-free!  

  • Regularly Check for Updates 

Machine learning is getting advanced now and then.In this scenario,only practical machine learning algorithms can develop over time if routinely checked and modified. Make sure the system is consistently checked for correctness and changed as necessary. 

  • Including Human Expertise 

Instead of replacing human knowledge, machine learning should be used as an instrument to supplement it. It should be the organizations’ duty to ensure the system is created to collaborate with human knowledge to maximize efficacy.  

  • Be Certain of Regulatory Compliance 

Organizations must make sure that any protection systems built on machine learning adhere to all applicable laws and standards. 

Conclusion for ML Enhancing Cyber Security

Machine learning has become a potent instrument for enhancing defense. Machine learning algorithms can automate danger identification and reaction, increase accuracy, scalability, and adaptability, and analyze enormous amounts of data in real time.  

But, to maximize the efficiency of machine learning in cybersecurity, organizations must handle issues like data quality, interpretability, and over-reliance and put the best practices for implementation and administration in place! If you also want to establish a secure web space for your organization, machine learning should be on your list to advance cyber security for your firm!  Hence, it is rightly said that ML is enhancing the cyber security. 


AR and its influence on the customer’s decision

Augmented reality or amplified experience of the real world is a new emerging tech concept, and AR influence customer’s decision. It is widely discussed and applied in innovative devices to improvise automation in lives. Today, it can be seen in watches, high tech movie experience, gaming and whatnot! 

The technology is continuously advancing and is implementing modern applications. It was just yesterday’s story when AR got hyped and today, its increased popularity can be accounted for by its influence on critical steps of customer journey and customer experience. 

Not only this, it is being widely realized that products with AR (augmented reality) wins the market faster.  

Why AR?

In a survey, 61% of consumers said that they would prefer products that can be customized with AR

And if your customers like it, it’s already in demand. But what makes AR such a project worth investing in? 

The major reason behind its success is its ability to enhance and improve user experience. Games, software, logistics all brought up with AR provide end-users with a lot of different experiences. And when the user experience is advanced, the user feels engaging and gradually inclines towards it. 

AR Influence customer’s decisions 

Think of yourself as an average customer and shortlist your decision-making points. You will probably put “experience” at the top of the list. 

That’s where Augmented Reality influences the decision-making process of the customer. As it significantly advances the user experience throughout the software or product usage, its right implementation can deliver value to users and hence, AR influence customer’s decision. 

Think of two gaming worlds. One incorporated with AR and let you experience the dinosaurs and other creatures of the jungle world while another one is just a game world motioning over a LED screen. 

Able to Interact with dinosaurs will definitely  be the major choice. That’s how AR lets you rule the customers. 

AR: The Future

AR shows signs of a pragmatic future. The day is not far when we all will be able to order food at restaurants with enhanced AR-driven menu options. Not only in real life, but applications of AR in logistics, and tech-driven hardware devices are also very progressive and will go to some amazing dimensions. 

AI Healthcare

Conversational AI and its Positive Impact on Healthcare

Healthcare is an industry that faces a plethora of challenges. Be it in terms of patient handling, discovering new drugs, catering to the needs of patients with chronic diseases, and whatnot. Earlier, major healthcare challenges were believed to be solved by appointing more doctors or increasing consultation hours. But, this resulted in an increased load on doctors. And, ultimately didn’t help the whole situation.  

This highlighted the need for a system that would solve all challenges and not burden doctors, and healthcare staff more. Conversational AI in Healthcare branched the right advantages for this. And only a few years after its implementation in healthcare, it is providing some beneficial applications. Let’s hop on to discuss this in sheer detail. 

Virtual Assistants: Conversational AI’s Real Heroes

Virtual agents that can help patients online or via their devices are the best applications of conversational AI. These agents can help patients 24*7, can provide them with multilingual support, and so forth. These agents can also let patients get first aid medical help in unfavorable times, and at unusual hours. 

These play an important role while bridging the gap between patients, and doctors. From diagnostics to treating diseases, VAs are slowly streamlining healthcare. Conversational AI agents also assist in maintaining patient support, delivering online consultations, supervising prescription records, analytics generation, etc. 

These agents help healthcare facilities, doctors, helping medical staff, and patients as well. And, as per the reports, the healthcare virtual assistant market is expected to reach $1.7 billion by 2025! Let’s now discuss some of the recent developments in healthcare that are taking modern healthcare a level up!

Recent Developments in Healthcare 

Technology, AI, or conversational AI specifically is evolving every day. And, scientists are leaving no stone unturned to take today’s healthcare a level up. Let’s comprehend some of the new progress in healthcare– 

  • In 2017, HealthTap by opening an Asia Pacific Hub Office in Hamilton, New Zealand connecting New Zealanders with neighboring healthcare clinicians. This was through their phones, tablets, or personal computers. 
  • In 2018, a cloud-based speech recognition program was launched in Canada. Launched by Nuance, Dragon Medical One enabled physicians to rapidly capture a patient’s complete history! 
  • Introduced by Verint Systems and UCB, April is an app that has a patented and conversational virtual health assistant. 

One more AI-powered virtual health assistant is launched by Gravitas AI. TINA, developed on robust AI & ML principles, is helping a number of healthcare facilities, and professional doctors all over the country. 

It can gather data, deliver patient support & assistance 24*7, and can cater to patients of different locations due to its multilingual feature. It is platform agnostic, and hence propound no hassles in integration and deployment. Further, TINA can be customized according to your needs, and requirements which make it one of the best available conversational AI agents. 

Conversational AI: a Tomorrow for Healthcare 

With the speed with which healthcare is moving towards digitalization, conversational AI indeed is the future. The virtual assistants providing first-line support to patients, and helping doctors automate their regular tasks is commendable. 

The future of healthcare is indeed digital. And, conversational AI agents are an important contender. If you also want to leverage these agents for your healthcare business or want to deploy them in a hospital or your clinic, meet the team of Gravitas AI today! 


COVID-19: Utilizing Artificial Intelligence in the Wake of the Coronavirus Pandemic

The novel Coronavirus has brought the world to its knees. As the number of positive cases and deaths keep rising, and mankind awaits an FDA-approved drug, frontline workers in the fields of healthcare and technology are constantly striving to come up with effective solutions.

Artificial Intelligence is providing strong support to the healthcare ecosystem!

Virus Diagnosis

E-commerce behemoth Alibaba has come up with an AI platform to fight this global pandemic. This is a diagnosis system with 96% accuracy, they claim.

According to the company’s cloud-based business unit, the platform can help frontline medical workers diagnose the virus in seconds.

Drug Development

Developing drugs is a tedious process and easier said than done during a pandemic. The time to market for an effective drug is about a decade with a failure rate more than 90%.

Thankfully, Artificial Intelligence can help in accelerating this process and make drug development quicker, cheaper and more successful.

Google’s DeepMind is leveraging the potential offered by AI to understand the protein structure of the novel Coronavirus.

Similarly, South Korea-based Deargen is using MT-DTI, a deep learning model that makes use of simple chemical sequences instead of 2D and 3D molecular structure of the protein to figure out it’s binding affinity to a target protein.

Delivery of Medical Supply

To reduce human to human interaction during the COVID-19 pandemic and still deliver medical supplies on time, AI-powered intelligent drones are being put to use.

Companies such as Terra Drone are using these tech marvels to carry medicines, samples and quarantine materials and even to patrol public spaces with the help of thermal imaging.

Hospital Chores

Robots are being used to supply medicines, deliver food, clean, sterilize and perform other hospital chores. This is a welcome change when the need for social distancing is highly warranted, but reducing human to human interaction is kind of difficult inside hospital premises.

Companies such as Blue Ocean Robotics are supplying UVD robots that use UV rays to kill germs. Others such as those from Pudu Technology are being deployed to cater food. Overall, it’s a collective effort.

Another company called Ant Financial is offering a blockchain platform that speeds up processing of healthcare claims to minimize the interaction between hospital staff and patients.

Content Moderation on Social Media

This is a bigger challenge than we can imagine. Content moderation is needed to maintain calm and peace during a pandemic. Social networks need to be policed regarding sharing of sensitive, fake and unwanted news related to COVID-19.

Recently, Facebook, Google, Microsoft, Reddit, Twitter, YouTube and LinkedIn jointly announced that they are going to work closely on COVID-19 response efforts. The idea is to promote trusted content and remove any kind of misinformation.

Information Provision

Accessing the right information about the novel Coronavirus is of utmost importance. This is where AI-powered chatbots can be used. They have the potential to offer day and night 2 way communication tirelessly to keep people updated with the latest, specific and required information on the Coronavirus pandemic.

At Gravitas AI, we are using conversational AI to facilitate information provision through trusted sources. This is our humble contribution to this battle against the virus through our highly advanced algorithms. We currently have 3 versions of the bot : a) for global audiences using advisory from the World Health Organisation b) for UK citizens, using advisory from NHS UK and EU and c) for Indian citizens using advisory from the World Health Organisation and Government of India. We have developed our product as a not for profit initiative with an aim to provide accurate information to the subscribers. We are not charging for our efforts or intellectual property. Instead we are offering this product to the organisations for a minimal fee to cover the cloud and platform costs.

Get your Facts Right!

Here’s what the World Health Organization (WHO) says about COVID-19:

What is Coronavirus?

Coronavirus (CoV) is a collective family of viruses causing a range of illnesses including the less severe common cold and other severe diseases such as Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV).

All Coronaviruses are zoonotic. They can jump species and are transmitted from animals to humans. For instance, SARS-CoV has been found to spread to humans from civet cats while MERS-CoV from Arabian camels.

What is COVID-19?

Coronavirus Disease 2019, aka COVID-19 is the newest strain belonging to the Coronavirus family that was discovered in 2019. This is a novel strain that has not been identified in humans earlier. Its source is not yet known.

How does the COVID-19 Infection Spread?

The COVID-19 virus spreads mainly via respiratory droplets. These droplets carrying the virus can be transferred from an infected person’s mouth or nose to a healthy person nearby. Alternatively, the virus can also spread via contact with contaminated surfaces

What are the symptoms of COVID-19 Infection?

Common symptoms of a COVID-19 infection include the following:

· Fever

· Cough

· Tiredness

· Headache

· Shortness of breath

· Difficulty in breathing

Symptoms such as pneumonia, severe acute respiratory syndrome, kidney failure and even death are possible in severe cases of the infection.

Is there any Treatment for COVID-19 Infection?

Currently, there’s no known vaccine or treatment available to treat a COVID-19 infection. Supportive care is however available for those who are infected.

How to Prevent the Spread of COVID-19 Infection?

Since, there is no cure at present this is the most important part. The spread of COVID-19 infection can be prevented by following the below mentioned recommended hygiene practices:

· Regular washing of hands with soap or liquid hand wash.

· Frequent use of alcohol-based hand sanitizer

· Covering your nose and mouth with your bent elbow while coughing and sneezing

· Using tissues when coughing and sneezing and disposing it of safely

· Avoiding contact with people showing symptoms of the disease

· Maintaining social distancing and a distance of 1 meter (3 feet) from people

· Avoiding large social gathering altogether

· Consuming thoroughly cooked meat and eggs

· Not touching your face, eyes, nose, and mouth

· Staying home if you are unwell

· Self quarantining if you’ve travelled to places hit by the Coronavirus outbreak.

· Self quarantining if you believe you could be infected

Wise men say self-help is the best help. If everyone does their bit in following the aforementioned practices, they can contribute to the safety of others.

Researchers and workers in the field of healthcare and technology are doing their utmost to beat the novel Coronavirus. All you need to do is make sure you stay aware, take a step back and save mankind.

Mukesh Kumar Sinha, CCO & Co-Founder, Gravitas AI



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