Artificial Intelligence has a vast scope of utility to expedite processes and augment human productivity. Auditing business processes in a heavy document-laden environment is just one of them. Auditing is the cornerstone of quality-driven enterprises, where they have to frequently scour through paper logs and documents generated at the end of each intermittent process. Sampling as a part of the audit tool leaves scope for error. However, using Artificial Intelligence (AI), more specifically Deep Learning enabled process automation in the auditing realm allows to audit almost the entire universal data set.
How do AI and Deep Learning benefit auditing?
AI or Deep Learning allows generating text summaries in the most integrated form. As data explodes and generates high amounts of free-text data, auditing in the traditional sense seems next to impossible. AI / Deep Learning enabled mechanisms to allow to effectively curate and summarize data. Deep Learning uses Advanced Natural Language Processing (NLP) and Deep Neural Networks (DNN) to generate a new summarized logical sequence of words and sentences without changing the meaning of the text. The summarized data is tagged to the digitized asset as metadata that not only allows seamless auditing but also seamless storage, search, and retrieval. Deep Learning follows an Extractive Approach or an Abstractive Approach to generate the text summaries.
>> Accelerate product reviews with Deep Learning and Natural Language Processing
What are Extractive and Abstractive Approaches in Deep Learning powered Text Summarization?
Extractive Summarization copies parts of sentences from the source through measured weights of importance and subsequently combines them to form a summary.
Abstractive Summarization generates new phrases by first understanding the text and then rephrasing words in the source in a condensed format. It is the toughest among the two approaches.
Abstractive Approach proves to be superior of the two
Extractive Approach though an old technique in the field of auto-summarization is not summarization per se. When human beings summarize content, they read the content in its entirety and then summarize by creating key takeaways of the overall content. The extractive Approach, however, deals with only word weights.
The abstractive Approach on the other hand uses NLP and DNN algorithms to build sequential and logical statements as humans would. NLP and DNNs offer better scope and quality results in comparison to the Extractive Approach.
Read – Whitepaper on how Deep Learning enabled Text Summarization enables audits
DNN sequencing in Text Summarization
DNNs use a sequence to sequence model while predicting a new sentence. One type of DNN is Long Short Term Memory (LTSM) that is used for Abstractive Text Summarization. LTSM is a recurring neural network. It uses LTSM cell blocks instead of neural network layers. It feeds the output of one LTSM block at time T as input to the same LTSM block at T+1. These neural networks are programmatically unraveled during the training of the algorithms. In this process, a new word or the output from an earlier cell is fed to the network at each time step. Thereby a new word is sequentially concatenated to the earlier output. This DNN framework predicts new words and sentences such that the LTSM progressively builds the Abstractive Text Summary. This framework uses a unique encode-decode model for building text summaries. This encode-decode model is trained in tandem to read the source and generate the summary.
Simply put
AI or more specifically NLP and DNN algorithms offer a competent model for creating summaries from vast arrays of unstructured documents. The model is adept at summarization of long documents and creating crisp summaries that can be attached as metadata and executive summaries to the digitized asset. In effect, the auto-summarization powered by AI makes auditing assignments quick and easy.
. Over the years, technology has enabled the business to capture a huge amount of data from various sources in real-time, empowered the stakeholders to make sense of the insights, and make data-driven business decisions. Today, research and consultancy firm McKinsey estimates that leveraging Big Data can generate up to $100 billion annually in the US Healthcare system.
As the technology became more advanced and accessible, data analytics for healthcare extended to Pharmaceutical companies that saw great potential and an opportunity to accelerate critical aspects of core business such as drug discovery, patient trends. Pharmaceutical is a domain that has fierce competition with companies racing for drug patents and hence to extract the best results out of data analytics, the market research and drug innovation teams are finding newer ways to empower the business and gain critical competitive advantage by leveraging different data analytics tools. Let’s take a look at different ways Pharmaceutical companies are leveraging data analytics to drive value.
A. Drug Discovery & Development
Accelerating the drug discovery process is critical for Pharmaceutical companies that are always on the cusp of occupational hazards such as expiring patents. From the initial research to the final launch, t is estimated that an investment of a few billion dollars ($3bn to $5bn) goes into new drug development. Today, businesses are always in the search of finding better ways of using data visualization tools to interactively display vast data collected from recent patents, medical journals, and published media from researchers. Unlocking hidden insights from such data is critical for companies to optimize their drug development process and Pharmaceutical giants such as Sanofi, Bayer, AstraZeneca are already betting big on data analytics for healthcare to help them win the drug launch race!
B. Leveraging Predictive Modeling
The importance of accurately using a data visualization platform to identify which attributes of a patient’s health qualify for the use of a particular drug cannot be overstated! The industry has seen a meteoric rise in companies analyzing data such as patients’ lifestyles, genetics, and existing disorders to predict risks and drive therapy focusing on critical neurodegenerative and cardiovascular medical conditions. Linking the possible risks of particular drugs to the medical conditions ensures the patient does not intake medication that may prove fatal in the long run. Companies that specialize in data analytics services are thus empowering the Pharmaceutical companies to invest in drug discoveries that have more upside in the future.
C. Improving Clinical Trials
Clinical trials form an important aspect of any successful Pharmaceutical company. It is also a process that requires a huge investment of time and money and is often dependent on external factors such as the right mix of patients, accuracy of data, etc. Big Data has been instrumental in identifying the right demographic and analyzing historical data to form the best-suited group of a patient for the clinical trials thereby improving the end-results. Data collected during the process such as genetic background, side-effects, medical monitoring is also useful to the researchers and leveraging data visualization software to intuitive showcase charts and reports enables the stakeholders to get the accurate representation and make informed conclusions.
D. Effective Patient Profiling
Due to the global adoption of Electronic Medical Records (EMR/EHR) critical medical sensors, drug treatment data is available easier than ever before. As patient treatment improves, medical practitioners, as well as Pharmaceutical companies, have realized that the one-drug-fits-all approach is no longer the best way to go forward. Analyzing this data has empowered Pharmaceutical companies to dig deeper and extract patterns and trends to target their development efforts. Such data is also useful for business owners and product heads to decide drugs that are given to patients with common disorders or specific medical conditions. Companies such as Pfizer are already investing big in data analytics and visualization software to drive their targeted efforts.
Impact of Investing in Data Analytics for Pharmaceutical Businesses
Optimize the product pipeline.
Reduce the cost of the drug development process.
Enhanced Clinical Trial Feedbacks.
Predict disease trends and patterns.
Improve medical forecasting.
Improved drug launch cycle.
ITCube’s product and IT services have enables healthcare businesses around the globe to optimize their business processes and align them with the desired business outcomes. Get in touch with our experts at [email protected] to know how our dynamic and robust data visualization software ITLytics can empower your organization to gain a competitive advantage and prepare for the upcoming decade.
Sleep is a crucial practice for maintaining one’s health. In a survey, it is recorded that 62% of adults feel that they don’t sleep well, because of various problems such as stress, worry, work schedules, health conditions, and disruptors (Bad Habits), etc. Through constant exercises and a good daily routine, an individual can nurture his/her health. This is where Fitness activity and sleep tracking apps in mobile apps development come into play.
Sleep deprivation can cause several long-term diseases:
1. Heart disease and Heart failure
2. Weak immune system
3. Kidney diseases
4. Depression
5. Diabetes
The only possibility for having a good sleep is to keep oneself free from stress and worry because they are the main reason for sleep deprivation. As mentioned before, exercises and a good daily routine can aid in eradicating sleep deprivation.
The majority of the adults hit the gym for maintaining their health, but some individuals are held back from doing so because of work or school schedules. Since technology had taken over the world, it has helped people to live their lives seamlessly.
Hence, fitness activity and sleep tracking apps in mobile apps development aid individuals to outline their day to day routine and assists in tracking their progress for both body and sleep activity.
There are several successful activities and sleep tracking apps in the market today, providing excellent services, some of them are:
1. Google fit
2. Map my fitness
3. Charity miles
4. The Johnson & Johnson official seven-minute workout
5. Fitbit
6. Sleep cycle alarm clock
Fitness activity tracking correlates with the sleep tracking feature of the app for providing the user’s all-round health maintenance because it is an individual duty to maintain his/her health.
Development of Fitness Activity and Sleep Tracking Apps in Mobile Apps development:
The development process includes front-end development, back-end development and the final process of deployment.
1. Front-End Development – Designing:
The Front-end development of an app includes User Interface (UI) & User experience (UX) Design as they are of supreme importance in the software or application development process. UI and UX design are the foundation of any app or software being built. UI is the aesthetics of an application. In simple words, it is the appearance i.e. style, font, and color, etc. of an application. A Good UI designer will go through a long and exhausting process of understanding the requirements and expectations of the end-users and design an application that can aesthetically satisfy the end-user. UX is the user’s emotion or attitude on using the app. UX process is extensive, which includes many important processes like wireframing and probing. User Interface & User Experience together are essential in furnishing an application both aesthetically alluring and seamless.
2. Back-End Development – Development:
Back-end development is the key process, in the rendering of fitness activity and sleep tracking apps in mobile apps development. Back-end development includes programming. The developers work hard in developing the app according to the expectations of the end-users. UX Designers support the back-end developers in achieving a seamless sensation. They guide the developers to furnish an application according to the data analyzed – the wireframes and prototypes.
Deployment Platforms:
The platform should be determined beforehand so that the designing and the developing process would be executed accordingly, for example, Android, iOS, Blackberry, etc. Different platforms have different programming languages hence the specifications should be decided beforehand.
Features to be included in the fitness activity and sleep tracking apps in mobile apps development:
1. Sleep Tracker:
Sleep Tracker is the most essential feature to consider while developing an app because it offers a variety of data including sleep patterns, heart rate, blood oxygen levels, breathing patterns. Mobile apps of this sort use sensor to recognize the action when the user sleeps and render insights about the user’s sleep patterns to help them sleep healthy.
2. Workout and Exercise Tracking:
Fitness is a wise way to live a healthy life. Nowadays, people with obesity problems and low weight are prone to heart diseases and diabetes. Workout and calorie counter features are used by individuals to live a healthy and sound life. Fitness apps are already using this feature to help people conquer fitness goals by recording calories consumed and burned, providing fitness coaching and healthy recipes for a perfect diet.
3.Reminders and Notification:
The app should be equipped with a reminder and push notification feature to help prompt the users about the workout session. The reminder and notification feature of the app is a crucial feature for such apps. In our engaged lives, our routines can be forgotten hence reminders and notifications can help us be conscious of our routine and assist us in following the activities without fail.
4. Food Diet Tracker:
Food diet tracker is a helpful feature for the user because it helps the users to keep track of what they consume and the number of calories they consume regularly. Users can keep track of how many calories they consume and maintain food consumption and can live a healthy lifestyle. This feature should also offer users with healthy recipes for a balanced and healthy diet. This is one of the most important features to be included in fitness activity and sleep tracking apps in mobile apps development.
5. Setting goals and tracking:
Setting goals and tracking feature can help users set goals on their fitness objectives and can keep track of their achievements. Users can calculate time, distance, speed from the records and can keep track. Users can get notified about their workout goals and can track their progress in real-time.
These are some of the features, the fitness activity, and sleep tracking apps in mobile app development can offer its user, these features of the application assist the users to live a healthy lifestyle.
It’s always better to overexplain than underexplain.
Why? Because going back and re-doing something you’ve spent days, if not weeks, creating, is decidedly not fun.
We all know that communication is the cornerstone of any working relationship — but it’s even more important for a designer handling big projects.
Communicating your vision & ideas in a clear way is the foundation of doing the work correctly.
And it means the difference between doing a one-week project in five days vs in ten.
An essential tool for a designer communicating with their clients is prototyping, as it cuts down the risk of redoing your work all the time.
Definition of Prototyping for UX Design
There are various definitions of prototyping, but let’s focus on the crucial meaning.
Prototyping is simply creating a low-effort, low-fidelity object which reflects what we want to design in the end. Its purpose is three-fold:
Test how your design will look and feel like
Explore and change things around without spending much time on it
Communicate what the final product will look like to everybody interested
Your prototype will differ from mine but generally prototypes range in fidelity/effort to make them from the simplest sketch to an interactive wireframe with clickable modules.
For each project, you’ll have to figure out what kind of prototype you’ll need to communicate your design know-how perfectly.
When to create a prototype first
While it seems natural that prototyping should be ubiquitous, there are some tasks that particularly cry out for extensive prototyping first.
When you’re designing across multiple devices.
The reality of work as a designer for software products today is that our work will likely be used across devices.
This means that in order for us to make our stuff excellent, we need to take into account not just different screens, but also wildly different modes of input: the users will use touch, remote control, keyboard & mouse — whatever you can imagine users employing to interact with your product.
And it’s not likely that there will be fewer types of input in the future — the opposite, in fact!
In designing across multiple types of input devices and forms of interaction, the prototype is our best friend.
Added to that, various prototyping apps allow you to showcase your prototypes on differing devices, which helps you to:
Test your design on actual users in the format they’ll likely be using your designs.
Provide your clients with a clearer view of the holistic approach to design.
When you’re designing a new structure/informational architecture
When designing for a product/website with a huge content load, a simple sitemap diagram might simply not be enough. Besides, a diagram doesn’t allow you to go ahead and test the structural elements you’re developing.
Let’s zoom in for a second, and we’ll see that without a proper prototype with in-built interactive elements (even if perfunctory) it’s very tough to actually test and present how the structure is supposed to work, and what behavior the user is supposed to display.
However, with an interactive prototype, any informational architecture will be considerably easy to test out.
By providing our users (i.e. experiment subjects) with real buttons and modules to click on, it will give us a much more accurate picture of user behavior.
Both the clients and the potential users will have a much more visceral, tangible experience with your potential product.
That benefit of visualization and real exploration makes selling your idea much easier.
When you’re designing interactive elements
Any website page and any app have at least a single interactive element, be it a link or a button.
But the vast majority of things we design in 2021 will have a lot more interactivity.
For example, think about a website selling clothes and accessories. Users tend to have varying requirements in narrowing their clothing searches, whether it’s by size, color, season, garment type, fabric, brand, and so on.
This means that we’ll need to design filters and create advanced navigation patterns. And trust me, this is not easy.
Being able to mess around in the prototype saves a whole lot of time because you’re essentially designing the elements without spending any extra effort.
The Principles of Prototyping
In order to make your prototype correctly, you need to have a plan first.
Principle #1 — set your goals first.
Your goals for your prototype should be very specific. For example: “Explore five UI ideas to improve conversions from the initial login step of the checkout process”.
This goal is specific, measurable, and at the end, you’ll have on your hands a working way to increase the conversions, which is what you’ll be after the entire time.
Remember, though, that your goals will change in the process, and that’s okay too!
Principle #2 — know when to stop.
The entire purpose behind prototyping is to save time and money on designing an entire project.
But it’s easy to get carried away, so you’ll have to set some boundaries. You definitely don’t need to recreate the entire app if you’re only designing one module for it.
On the other hand, when creating a new website architecture/navigation from scratch, you might have to map out every single nook and cranny of that website.
To know when to stop, you need to consider how your prototype will fit into the whole of the object you’re building, and place appropriate placeholder content where needed.
Principle #3 — know what you’ll use your prototype for.
A successful prototype is not the most filled-out, nor is it the one that was the quickest to do. The best prototype is that which fits its purpose perfectly.
In other words, consider your audience. If you’re making an early-stage design with your close collaborators, making your prototype detailed is out of the question, as most anything will really do.
In that case, you can prototype using Powerpoint/Keynote, InVision, or Marvel.
On the other hand, when you’re working with a bigger company or your direct clients, you’ll need something that works not only for you but for them as well.
Principle #4 — it’s going to be quick and dirty.
As far as I’m concerned, the most important point of prototyping is to do it. Prototyping is fast, cheap, and aimed, appropriately, at saving time and money.
For a designer, it might be tough to accept that the object you’re designing is going to look subpar, but the reality is that prototype is made to be changed, edited, thrown out.
As you’re prototyping, you should have the mindset that everything can and will be cut if needed.