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Why Is Medical AI Gaining Prominence?

Outbreak of new diseases puts immense pressure on the healthcare system. Factors such as limited resources, a sudden rise in the number of patients, lack of established treatment, and vulnerability of medical staff add to the pressure on the healthcare system. In order to combat the outbreak of new diseases effectively, healthcare professionals require faster diagnosis, rapid response, effective use of human resources, and ensuring the safety of medical personnel.

In this scenario, medical AI is proving to be of immense use. Although the use of medical AI is not a new concept, the applications of medical AI have widened with the outbreak of new diseases and pandemics such as COVID-19.

  • Diagnostics: Diagnosis of some diseases may require the doctors to compare a large number of CT Scans, check medical history, or other detailed reports. This is a time-consuming process and may result in delayed treatment causing negative effects, specifically in time sensitive cases. AI software helps in analyzing large amounts of patient data to assist doctors in diagnosing patients at a greater pace. This assists in lowering the treatment time.
  • Risk Profiling: In the case of diseases that are contagious and spread easily, it becomes imperative to track the patients, travelers, tourists, etc. This helps in building a risk profile of the individuals. But manual profiling is time-consuming and prone to errors. On the other hand, AI-based risk profiling software has capabilities of historical geolocation and anomaly tracking of individuals in an efficient manner.
  • Optimizing Drug Therapy: Effective and proper treatment of a new bacterial or viral infection requires a combination of different drugs. However, the process of searching for suitable drug molecules can be laborious, time consuming, and costly. It also requires numerous trials and can involve manual errors. AI-based systems help in optimizing the drug discovery process by searching the databases of complex drug molecules and matching the drug molecules with the target proteins. This reduces the research time and increases efficiency.
  • Assistance For Medical Staff: AI-based apps can help the healthcare staff in gathering relevant information such as hospital-specific information, latest guidelines, operational directives, new treatments, protocols, drug dosage, and drug formulary. Well-trained AI systems can be used to analyze a patient’s reports and assign the case to a relevant specialist in the hospital.

For more information on increasing applications of medical AI, call Centex Technologies at (972) 375 - 9654.

Why Is Medical AI Gaining Prominence?

Outbreak of new diseases puts immense pressure on the healthcare system. Factors such as limited resources, a sudden rise in the number of patients, lack of established treatment, and vulnerability of medical staff add to the pressure on the healthcare system. In order to combat the outbreak of new diseases effectively, healthcare professionals require faster diagnosis, rapid response, effective use of human resources, and ensuring the safety of medical personnel.

In this scenario, medical AI is proving to be of immense use. Although the use of medical AI is not a new concept, the applications of medical AI have widened with the outbreak of new diseases and pandemics such as COVID-19.

  • Diagnostics: Diagnosis of some diseases may require the doctors to compare a large number of CT Scans, check medical history, or other detailed reports. This is a time-consuming process and may result in delayed treatment causing negative effects, specifically in time sensitive cases. AI software helps in analyzing large amounts of patient data to assist doctors in diagnosing patients at a greater pace. This assists in lowering the treatment time.
  • Risk Profiling: In the case of diseases that are contagious and spread easily, it becomes imperative to track the patients, travelers, tourists, etc. This helps in building a risk profile of the individuals. But manual profiling is time-consuming and prone to errors. On the other hand, AI-based risk profiling software has capabilities of historical geolocation and anomaly tracking of individuals in an efficient manner.
  • Optimizing Drug Therapy: Effective and proper treatment of a new bacterial or viral infection requires a combination of different drugs. However, the process of searching for suitable drug molecules can be laborious, time consuming, and costly. It also requires numerous trials and can involve manual errors. AI-based systems help in optimizing the drug discovery process by searching the databases of complex drug molecules and matching the drug molecules with the target proteins. This reduces the research time and increases efficiency.
  • Assistance For Medical Staff: AI-based apps can help the healthcare staff in gathering relevant information such as hospital-specific information, latest guidelines, operational directives, new treatments, protocols, drug dosage, and drug formulary. Well-trained AI systems can be used to analyze a patient’s reports and assign the case to a relevant specialist in the hospital.

For more information on increasing applications of medical AI, call Centex Technologies at (972) 375 - 9654.

Building Your First Start-Up App

Every start-up faces two main challenges - testing the risk assumptions and collecting the maximum amount of validated information with the least efforts. Your first start-up app should offer solutions to these two challenges. There are no set layouts on how your first app version should look, however, there are two main guidelines every entrepreneur should be aware of:

  • It Must Be An Answer To A Problem: The goal of first app version is to find out if your unique feature is valid enough to help you compete against the existing competitors in the market. Make it a point that app features should present the core of your solution in a compelling light. If the users are not convinced by the value of the core solution, they would not care to switch even if you provide add-on features.
  • It May Not Be Automated: While automation may be a good feature to be included in an app, the first version of your start-up app need not be automated as far as it solves the user’s problems and allows you to test the risks. The purpose of your first app version is to help you de-risk the start-up and build your business on a stronger foundation.

Additionally, there are some key characteristics that you should keep in mind for building a successful start-up app:

  • Simple To Use: The first and foremost characteristic that accounts for the popularity of an app is the simplicity to use. While it may be tempting to incorporate a lot of interesting ideas and third party widgets, it is important to keep in mind that the app will be used on mobile devices with limited screen dimensions. Thus, provide a simple user interface that is easier to use.
  • Abolish Clicks: Attracting users to your app is important; making them stick to your app is equally necessary. Although, collecting user information is one of the underlying purposes of a app, do not overwhelm the users with multiple questions. Try to ask a minimum number of questions, banish unnecessary clicks, and avoid multiple taps in navigation.
  • Multiple Device Compatibility: It is understandable that users are most likely to access the app on mobile devices so, make sure that your app is compatible with all the popular Operating Systems used across mobile devices such as iOS, Android, etc. Also, try to keep your app compatible with up to 2 versions prior to the latest update of these operating systems.
  • User Feedback: Be sure to include the user feedback section in the app. It will provide valuable information about how your app works, ease of use, and improvements that users expect.
  • Security: Security is crucial for the success of any app. Users will provide their details only if they are sure about the security of an app. So, pay attention to data security and other cyber security aspects of the app.
  • Analytics: Analytics will help you to track user behavior while using your app and shed light on the feature that accounts for maximum user retention. This will allow you to develop popular features and work towards making your app succeed.

For more information on building your first start-up app, call Centex Technologies at (972) 375 - 9654.

How To Implement A Successful Remote Work Strategy?

The number of employees working from home on a full-time or part-time basis has increased in the past few years. With the outbreak of the COVID-19 pandemic, this number has increased many folds. Although it is the need of time but working from home poses some challenges such as lack of face-to-face supervision, lack of access to information, distractions at home, sense of being left out, security breach, etc. This is exerting pressure on businesses to implement effective remote work strategies to tackle the challenges/risks and improve the efficiency of the workforce.

Here are some tips for implementing a successful remote work strategy:

  • Structured Daily Check-In: Remote managers should make it a point to establish a daily call with the remote employees. It may be an individual or team call based on the nature of individual work (whether the remote workers operate independently or in a collaborative manner). The aim of the call should be to provide a forum to the employees where they can discuss any work-related concerns and get an effective solution. The call can also be used as a platform to discuss daily goals and progress to keep a tab on productivity.
  • Provide Different Communication Technologies: Making use of different communication technology options can be imperative for a successful remote work strategy. Businesses should consider a video conference for maintaining a personal interaction between the employees. The video conference technology may be used for conducting complex or sensitive communications. The organizations can also make use of mobile-enabled individual messaging functionalities for handling simpler, less formal, or time-sensitive conversations. However, remote managers should make it a point to consult the IT department of the organization before making use of any communication tool to ensure data security.
  • Lay Out Ground Rules Of Engagement: Lay out clear rules to maintain uniformity of engagement channels among the remote employees. The rules should discuss the mode of communication to be used based on the nature of communication. It is also important to state a fixed time for team meetings and video conferences. Once the rules are set, the managers should monitor the communications to ensure that the employees are adhering to the rules and sharing information as per the directives.
  • Educate Employees On Data Access And Sharing Policies: A key challenge in implementing a remote work strategy is to ensure data security. So, remote managers should collaborate with the IT department to lay out strict data access, data sharing, and user login policies. Educate the employees about the data policies, data breach, ways to detect a cyber attack, etc. A good approach is to organize webinars for the team to provide the required information and acquaint the employees with the security protocols.

For more information on ways to implement a successful remote work strategy, call Centex Technologies at (972) 375 - 9654.

Making Data Analytics Human For Decision Making

Data intelligence is an important aspect of every organization. It lays the foundation for data analytics and decision making by the company executives. However, data collection and analysis are conducted by computers that store them in languages that are not comprehendible by humans. Thus, in order to facilitate decision making, it is imperative to make data analytics available in natural human languages.

Once the metadata is annotated in human languages, it provides information about events such as when, what, where, how and why they occurred. When the information is available in tangible form, it can be used to gain situational awareness and stimulate thinking by forming patterns or relationships between data. Formatting the data by forming visuals such as tables, charts, and graphs help in understanding the patterns and interdependency of various factors. This understanding defines the course of future actions to achieve desired organizational goals.

In order to understand how to make data analytics human for decision making, let us consider the following aspects:

Type Of Data:

Traditionally, metadata management focused on technical metadata including platform, structure and physical characteristics. However, as the business organizations are now relying extensively on data analytics, equal focus is being laid on collection and correlation of business metadata (business rules, associated applications, and business capabilities) and semantic metadata (business terminology and ontology).

Finding Data Patterns:

A large amount of data is collected on a daily basis. But in order to gain meaningful results, it is required to understand the relationships in the data. An example of data mapping for understanding interrelationships between entities, their properties and relationships is ‘Knowledge Graphs’ pioneered by Google. Although such graphs provide good information, they alone cannot be used for reliable decision making. Thus, more related data has to be collected from parallel platforms and databases to create a ‘Knowledge Platform’.

As the information is classified in classes and concepts across different datasets, it makes it easier to interlink and find related information. Businesses tend to make use of query languages to search for information across the contents of enormous datasets.

Narratives:

After understanding the patterns of data, the next step is to form a data narrative. It includes reasoning and learning in addition to data patterns. To create a narrative, it is important to understand three things:

  • Types of questions that may be asked based on data patterns
  • Answers to these questions
  • Questions that will arise based on previous answers

Data patterns may indicate information such as the effect of a variable on business metrics. But data narrative includes answers to questions such as ‘If metric goes up with time, how will it affect the business?’, ‘Does the metrics accumulate over time or is it point-in-time?’ and ‘What does it mean for our sales?’.

Decision Making:

The data narrative forms the basis of decision making. The decision makers of an organization analyze the narrative, visualize the supporting data, and test the hypothesis to identify gaps. The final decision conveys the required actions for achieving business innovation and goals.

For more information on making data analytics human for decision making, call Centex Technologies at (972) 375 - 9654.

Drug Discovery Through Artificial Intelligence

Artificial intelligence has garnered immense applications in various industries including banking, manufacturing, and healthcare. A branch of healthcare that is benefitting from Artificial Intelligence is the ‘Pharmaceutical Industry’. It is met with new challenges in the face of new viruses, mutated antigens, drug-resistant strains, etc. on a daily basis. Additionally, it has become common to see the rendition of once eradicated diseases such as polio. Under these conditions, traditional R&D can be very time consuming and costly.  

Traditional drug discovery methods are objective driven and work well for targets whose structure and interactions in the cell are understood. However, most of the cellular transactions have complex pathways.

In order to overcome these challenges, Artificial Intelligence-powered drug discovery offers an effective alternative. Following are the ways in which AI transforms the drug discovery process:

  • AI-powered drug discovery follows a data-driven approach that is based on the vast patient datasets. The data is studied and categorized by complex algorithms into understandable information for facilitating drug discovery at a faster pace.
  • It applies machine learning to study new incoming data for recognizing new opportunities and information.
  • The algorithms search through vast databases of compound structures to identify a compound that can bind to the antigen protein (even if the structure of the target protein has not been yet identified). This saves a lot of time when compared to manual screening of compounds that can act as drug candidates.

How It Works?

  • The first step is to take sample from people with and without a disease. Also, samples are taken from people who are at different stages of disease progression.
  • The sample data is then extracted into genomics, proteomics, metabolomics and lipidomics for identifying the target.
  • AI and Machine Learning software study the information to identify any differences between the disease and non-disease states, proteins, and other features that may impact the disease state.
  • The identified proteins and metabolites are considered to be target candidates by the software.
  • The candidates are then queried against databases of patents, publications, chemical libraries, clinical trials, and approved drugs. This facilitates a precision-medicine approach by offering a means to triage the patients in an in-silico manner before entering a clinical trial to determine the effectiveness of a potential drug.

Benefits Of AI-Driven Drug Discovery:

  • AI does not rely on predetermined targets which rules out the chances of subjective bias.
  • AI amalgamates the latest technology in biology and computing to develop algorithms for drug discovery.
  • AI offers high predictive power to define meaningful interactions in drug screening. This reduces the chances of pursuing false potential drugs.
  • AI moves drug discovery to a virtual lab where screening results can be obtained at a faster pace and efficiency.

For more information on transforming drug discovery through AI, call Centex Technologies at (972) 375 - 9654.