Pharmaceutical and biotechnology companies operate within a constantly evolving regulatory landscape, where adherence to standards set by organizations like the…
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Data Science & Analytics - Centre of Excellence
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What is Data Science?
Data science entails analyzing data to find patterns and characteristics.
A combination of mathematics, statistics, and computer science are involved here. A variety of visualization techniques are used to make the data understandable. The focus here is to gain insights that can make a positive difference to the organization by understanding and using the data.
Like natural intelligence, artificial intelligence enables computers to mimic the human intelligence and behavior.
Machine Learning is a branch of Artificial Intelligence that focuses on *learning. In order to learn autonomously from data, algorithms and statistical models are developed without explicit instructions being given up front.
Deep Learning is part of Machine Learning that uses artificial neural networks. Models of this type are based on the structure and function of the human brain.
Technologies at DS&A-CoE
Generate better Insights
with Cutting-edge Technologies
Machine Learning
Deep Learning
Natural Language Processing
Recommendation Engine
Visualization
Chatbot Development
Machine Learning
Machine Learning
By partnering with GenInvo’s Machine Learning expert team, you can build a system that helps you make better business decisions. ML techniques are revolutionizing clinical development, delivering time and cost savings and providing better insights to inform better decisions.
What it is and why it matters
In machine learning (ML), mathematical models of data are used to make a computer learn without being explicitly instructed. It’s a subset of artificial intelligence (AI). Machine learning uses algorithms to identify patterns within data, and then it uses those patterns to create a predictive data model. In exactly the same way that humans improve with more practice, machine learning results become more precise as the amount of data and experience grow.
A machine learning solution is an excellent choice in scenarios where the data is constantly changing, the nature of the task is changing.
Where does machine learning fit in?
- Predict values
- Identify any unusual occurrences
- Identify structure
- Make categories predictions
Use Cases
- Site selection for clinical trials
- Patient recruitment
- Lung Cancer Prediction
- Myocardial Infarction Complications
Deep Learning
Deep Learning
From labeling, training dataset assessment, and image processing, to custom deep learning pipelines, GenInvo Scientific develops deep learning for video/Image analytics, anomaly detection, and automation solutions in life science.
What it is and why it matters
Deep learning algorithms are capable of layering input data into layers of intermediate features, which is referred to as deep learning. Data are a major component of both biology and medicine, but they are often complex and difficult to understand. Therefore, deep learning techniques may be particularly well suited to solve problems in these fields. including the classification of patients
Where does deep learning fit in?
- Predict values
- Identify any unusual occurrences
- Identify structure
- Make categories predictions
Use Cases
- Lung Cancer Prediction
- Heart disease prediction
- Signature Detection
Natural Language Processing
Natural Language Processing
Utilize natural language processing pipelines powered by deep learning to extract meaning and insights from unstructured text, voice, and audio.
What it is and why it matters
A branch of artificial intelligence, natural language processing (NLP) assists computers with understanding, interpreting, and manipulating human language. It’s a science that combines computer science and computational linguistics, with the goal of closing the communication gap between humans and machines.
Where NLP fit in?
- Categorization of the content
- Modeling and discovery of topics
- Extracting context from the text
- Sentiment analysis
- Document summarization
Use Cases
- Text Similarity
- Name & Entity
Recommendation Engine
Recommendation Engines
Information systems that predict user preferences and presents product/item/service recommendations that are personalized and subjective.
What it is and why it matters
Recommendation engines filter data and recommend items based on machine learning algorithms in order to determine the most relevant items to a particular user. The program looks for patterns in consumer behavior data, which can be collected implicitly or explicitly.
Where does recommendation engine fit in?
- Content-Based Filtering
- Memory-Based Collaborative Filtering
- Model-Based Collaborative Filtering
Use Cases
- Recommender Engine – Algorithmically Predicting Anonymization
Visualization
Visualization
We have an experienced team for generation of Data Visualization charts with use of latest tools such as SAS, R, Tableau, Spotfire, Qlik Sense, and Power-BI.
What it is and why it matters
Data visualization refers to the presentation of data in a pictorial or graphical format. Decision makers can view analytics visually so that difficult concepts or new patterns can be understood. By combining interactive visualization with technology, you can drill down into charts and graphs for more detail, changing what you see and how it’s displayed as you go.
Where data visualization fit in?
- Identify relationships and patterns
- Acquire information quickly
- Pinpoint emerging trends
- Spread story to others
Use Cases
- Outlier detection tool
Chatbot Development
Chatbot Development
With our chatbot development services, you can offer customer support through human-like conversations to your customers, saving time and operational costs.
What it is and why it matters
Artificial Intelligence-based chatbots simplify human-computer interaction. With chatbots, computers can understand and respond to human input via spoken or written language. Conversational Artificial Intelligence is shaping the future of Life Sciences Interactions. With Chatbots and multi-channels integrations, businesses can meet their customer’s expectations by resorting to a new and improved way of interaction. Therefore, more businesses in Life Sciences are adopting Life Sciences Chatbots and leaving the traditional transaction behind. This is increasing the efficiency across the Life Sciences value chain.
Where chatbot fit in?
- Scalable Chatbot Applications
- Automated Transactions & Workflows
- Personalized Interaction
Why DS&A-CoE?
"Our aim is to accelerate discoveries and the development of life sciences worldwide using AI/ML"
Boost Innovation
The DS&A-COE is the GenInvo pillar and go-to place for AI. Our aim to accelerate discoveries and the development of life sciences across the worldwide using AI/ML. Our experienced and highly skilled business strategists, life science experts, data scientist’s and others understand tide of AI. We can assist in designing and implementing customized strategies to help traverse your business through a swift transition.
Increase Efficiency & Discover Insights Faster
Enables life sciences organizations to reduce time, eliminate data & process redundancies, minimize costs, wastages, and outflows. Enables you to drive efficiency in the business processes by delivering results in near real time, select the right target audience, and automatically classify and mine text for key insights. Real time results have made insight discovery faster than ever before. AI/ML generated results are more accurate and freer of any human induced errors or biases.
Mitigate Risks
AI where computer algorithms improve over time through their experience of using data – plays an increasingly prominent role in enterprise risk management. We create sophisticated tools to monitor and analyze behavior and activities in real time.
Case studies
Learn how our products and services are solving
business problems across industries
Building Solutions
Using AI/ML techniques, currently our experts are
working on to build solutions from scratch
