AI and ML Support Services
Our data scientists leverage machine learning techniques to analyze both historical and real-time data, uncovering trends and potential risk factors that can enhance diagnostic accuracy and treatment outcomes.
Data Analytics and Machine Learning
Our data scientists leverage machine learning techniques to analyze both historical and real-time data, uncovering trends and potential risk factors that can enhance diagnostic accuracy and treatment outcomes.
Precision-Driven Scientific Predictive Analytics
Our data scientists harness machine learning techniques to analyze historical and real-time data, identifying patterns, trends, and potential risk factors that enhance diagnostic accuracy and treatment outcomes. We collaborate closely with healthcare providers and payers, delivering valuable insights to improve business operations, personalize medical treatments, and support epidemiological studies for public health risk assessments.
Key Applications:
- Enhanced Diagnosis – Leveraging predictive models to support early detection and accurate diagnosis.
- Personalized Medicine – Tailoring treatment plans based on individual patient data for optimal outcomes.
- Surgical Risk Assessment – Predicting mortality risks in surgical procedures based on a patient’s condition.
- Optimizing Elective Procedures – Applying analytics to improve decision-making in scheduled medical interventions.
- Epidemiological Research – Identifying and preventing diseases through risk assessment and statistical modeling.
- Pharmaceutical Analytics – Analyzing drug efficacy, market trends, and treatment effectiveness to drive informed decisions.
AI and ML Services for the Life Science and Medical Sectors that we undertake.
Pubrica provides a comprehensive suite of physician writing support services designed to assist healthcare professionals throughout their research and publication journey. Our offerings are tailored to meet the specific needs of physicians and medical researchers, ensuring high-quality, efficient, and effective support. Here’s an overview of the services we provide:
- Annotation and Tagging: Manual and automated tagging of visual data for training machine learning models.
- Modeling and Algorithm Development: Development of convolutional neural networks (CNNs) and other image recognition algorithms to interpret and analyze medical imaging and video data.
- Image Analysis and Interpretation: Applying deep learning techniques to medical imaging (such as MRI, CT scans, and X-rays), Pubrica’s services include image segmentation, anomaly detection, and automated interpretation, aiding clinicians in making more accurate and faster diagnoses.
What tools are used for video and image analytics at Pubrica?
Pubrica utilizes advanced tools like OpenCV for image processing, TensorFlow and PyTorch for developing deep learning models, and specialized software such as MATLAB for algorithm testing and development.
What outcomes does Pubrica seek with video and image analytics?
The primary outcomes include enhanced diagnostic accuracy, improved patient care through better interpretation of medical imaging, and the development of automated systems for disease detection and monitoring.
- Natural Language Processing (NLP): Services include sentiment analysis, keyword extraction, and thematic analysis of clinical notes, research articles, and patient feedback.
- Algorithm Development: Crafting algorithms for information extraction, summarization, and translation of medical documents to support decision-making processes.
- Sentiment Analysis in Patient Feedback:Utilizing natural language processing (NLP) to analyze patient feedback and social media data, Pubrica provides insights into patient satisfaction, treatment effectiveness, and service quality, helping healthcare providers improve patient care.
- What tools are used for text analytics at Pubrica? Tools such as Python’s Natural Language Toolkit (NLTK), spaCy for advanced NLP tasks, and IBM Watson for sentiment analysis are commonly used to process and analyze text data.
- What data sources are used for text analytics at Pubrica? We use wide range of data sources that includes, The Internet of Things (think FitBit data), Electronic Medical Records/Electronic Health Records (classic), Insurance Providers (claims from private and government payers), Other Clinical Data (including computerized physician order entries, physician notes, medical imaging records, and more), Opt-In Genome and Research Registries, social media (tweets, Facebook comments, etc.) and Web Knowledge (emergency care data, news feeds, and medical journals)
- What outcomes does Pubrica seek with text analytics? Outcomes include extracting meaningful information from medical texts, improving patient care through insights gained from clinical notes, and enhancing research capabilities through better data interpretation.
- Voice Recognition and Processing: Implementing speech recognition algorithms to convert voice data to text, useful in-patient interviews and clinical documentation.
- Sentiment and Emotion Analysis: Analyzing tone and underlying messages in patient communications to better understand their health status and concerns.
- What tools are used for voice analytics at Pubrica? Pubrica uses tools like Google’s Speech-to-Text for converting speech into text, Kaldi for speech recognition, and emotion detection APIs to analyze vocal nuances.
- Statistical Modeling and Data Predictions: Utilizing statistical models and machine learning to make predictions based on numerical data, such as patient health metrics or population health tren
- Formula and Logic Development: Creating algorithms that apply complex mathematical formulas and logics to analyze and interpret large datasets, improving the accuracy of clinical research findings.
- Disease Prediction and Diagnosis: Utilizing machine learning algorithms to analyze historical health data, Pubrica develops predictive models that can accurately forecast disease onset and assist in early diagnosis, significantly improving patient outcomes.
- Genomics and Genetic Data Analysis: Leveraging AI to analyze genomic sequences, Pubrica helps in identifying genetic markers linked to diseases, predicting genetic predispositions, and personalizing medicine to enhance treatment efficacy based on individual genetic profiles.
- Drug Discovery and Development: Using AI models to predict molecular behavior, drug interactions, and treatment outcomes, Pubrica accelerates the drug discovery process by identifying potential candidates more efficiently and with lower initial costs.
- Clinical Trial Research: Enhancing the design and execution of clinical trials through AI-driven analytics, Pubrica optimizes trial protocols, patient selection, and data collection, ensuring more efficient trial management and more reliable results.
- Personalized Medicine: Integrating AI with patient data and current medical knowledge, Pubrica creates personalized treatment plans that consider individual variability in genes, environment, and lifestyle, leading to more effective treatment strategies.
- Healthcare Workflow Automation: Implementing ML algorithms to automate routine tasks such as patient scheduling, medical record management, and billing processes, Pubrica increases operational efficiency, reducing the administrative burden on healthcare providers.
- What tools are used for number analytics at Pubrica? Statistical software such as R and Python, with libraries like SciPy for statistical tests and scikit-learn for machine learning, are used to analyze numerical data.
- What outcomes does Pubrica seek with number analytics? Key outcomes include predictive modeling of disease trends, optimization of healthcare delivery through data-driven insights, and enhanced accuracy in clinical research findings.
- Cross-Data Insights: Integrating insights from video, image, text, voice, and numerical data to provide a comprehensive analysis.
- Algorithm Optimization: Enhancing the performance of existing algorithms for greater efficiency and accuracy in real-world applications.
- Tailored Solutions: Developing custom algorithms and models to meet specific research needs or clinical applications.
- Implementation and Scaling: Assisting with the implementation of these algorithms in clinical settings and scaling them to handle larger datasets or more complex analyses.
- Visual analytics, a crucial component of data science, combats information overload through advanced interactive visual interfaces and insightful data presentations. This process is driven by transformed data and user feedback, facilitating an iterative cycle that refines the visualization. Effective visualizations reveal hidden patterns, differentiate patient groups, identify key factors influencing diseases, and guide further analysis. Our data science experts collaborate with researchers to interpret data visually and meaningfully. Our reporting and visualization services include:
- Storyboard Creation: Structuring data stories to narrate the progression of findings clearly.
- Custom Templates and Graphs: Designing tailored visualization templates and graphs that best represent your specific data.
- Dynamic Charting and Posting: Utilizing advanced charting techniques and posting tabulations for enhanced data presentation.
- Modifications and Updates: Updating and refining existing data visualizations and graphs to reflect the latest analysis.
- Comprehensive Presentation Formats: Delivering insights in various formats including PowerPoint, Word, and PDF, suitable for diverse professional settings. <?li>
- Automated Reporting Tools: Implementing macro-driven tools for efficient and automated charting and reporting.
Pubrica ensure that every aspect of data, from collection to analysis, is meticulously managed and utilized to its full potential, fostering innovation and efficiency in medical research and healthcare operations.
How Do Artificial Intelligence and Machine Learning Modeling Services & Solutions Work at Pubrica?
At Pubrica, our Artificial Intelligence and Machine Learning Modeling Services are structured to deliver precision, adaptability, and innovative solutions tailored for the healthcare, medical, and life science sectors. Here’s how our comprehensive process unfolds, from initial data annotation to the development of sophisticated algorithms, ensuring compliance and delivering actionable insights:
The process begins with the meticulous annotation of data, which is essential for training machine learning models effectively. Our team handles diverse data types—ranging from images and texts to complex genomic sequences—ensuring they are accurately annotated based on the specific requirements of the project.
With the annotated data prepared, our data scientists and machine learning experts develop custom algorithms tailored to the specific challenges and goals of the project. This includes selecting and adapting existing algorithms or creating novel machine learning models that best fit the data characteristics and project objectives.
Throughout the process, we ensure strict compliance with relevant data protection and ethical standards, such as GDPR for data privacy and HIPAA for healthcare information. We also adhere to scientific standards such as FAIR (Findable, Accessible, Interoperable, and Reusable) to maintain integrity and reliability in data handling and model development.
The models are trained using the prepared datasets and continuously validated to assess their accuracy and effectiveness. Validation involves rigorous testing against separate validation datasets to avoid overfitting and to ensure the models perform well in real-world scenarios.
After validating the models, we use them to generate deep insights which are crucial for decision-making. Our team provides detailed reports and visualizations that interpret the model outputs in a meaningful way, making complex data understandable and actionable.
We provide comprehensive deliverables that include the final model, complete documentation of the algorithms, codebases, and an insightful analysis report. Additionally, we offer support for implementing these models into clinical or operational practices, ensuring that they deliver practical value beyond theoretical insights.
Pubrica guarantees the quality and accuracy of our AI and machine learning solutions with ongoing post-implementation support to adapt the models as new data becomes available or as project requirements evolve. This ensures sustained performance and relevance of the solutions provided.
Our Services
Specialized health economics services for informed decision-making and cost-effectiveness.
Patient journey and insights services to enhance healthcare outcomes and understanding.
Segmentation services for targeted healthcare strategies and improved patient outcomes.
Advanced predictive analysis services for data-driven insights and informed decision-making.
Expert algorithm development services for cutting-edge solutions in healthcare and research.
Interpretation & visualization services for clear, insightful data representation in research.
How Do Artificial Intelligence and Machine Learning Modeling Services & Solutions Work at Pubrica?
At Pubrica, our Artificial Intelligence and Machine Learning Modeling Services are structured to deliver precision, adaptability, and innovative solutions tailored for the healthcare, medical, and life science sectors. Here’s how our comprehensive process unfolds, from initial data annotation to the development of sophisticated algorithms, ensuring compliance and delivering actionable insights:


Speed up your journey to publication with Pubrica
Gain access to your personal assistant who will expertly guide you through intricate journal submission processes, shielding you from rejection and ensuring a faster path to getting your work published.
Guaranteed Quality
- In the rare case our work fails to delight you, we’ll re-work on it till you’re 100% happy.
- our commitment to excellence ensures reliable results and impactful outcomes in medical research.
On Time Always
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- Ensuring utmost data security through advanced encryption and strict protocols, offering peace of mind to all clients.


Frequently Asked Questions
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