- Deliver scientific outcomes faster by working with our experts in computational sciences.
- Reduce uncertainty in high-risk R&D initiatives by leveraging our industry experience.
- Keep up to date with the latest applications of machine learning.
- Up-level your team through collaboration with our experts.
Manifold’s contribution has been invaluable. Our integration of machine learning algorithms will enable the dynamic adjustment of treatment...
—Chief Medical Officer, Digital Therapeutic
Natural Language Processing
LLMs
Fine-tune large language models to your enterprise use cases
Semantic Search
Search and text retrieval over large document corpuses
LLM-Enabled UI/UX
Human in the loop UI/UX for query generation, plotting, cohort building, and more
Virtual Assistant
Natural language interface to chat with a corpus of documents
Structure Extraction
Extract structured data from unstructured clinical text data
Computer Vision
Image Processing
Process large-scale imaging data, including histology slides, CT, MRI, and video
Feature Engineering
Extract semantic features from images like nodule size or cell count
Synthetic Data
Use techniques from data centric AI to create more training data for machine learning
Semantic Segmentation
Segment images from your instruments, from fluorescence microscopes to CT scans
Multimodal Prediction
Forecast disease progression or response to treatment by combining genotype and imaging data.
Time Series
Digital Biomarkers
Develop digital biomarkers from multivariate time series data
Longitudinal Prediction
Predict disease risk or adherence from longitudinal patient data sources
Bayesian Modeling
Probabilistic time series modeling for forecasting and anomaly detection
Signal Processing
Discrete-time signal processing for linear and non-linear systems
System Identification
Dynamical system system identification using deep learning
Anomaly Detection
Unsupervised techniques to find anomalous patterns in time series data
Bioinformatics
QTL
Analyze genotypes and downstream traits to find associations for disease, drug response, or clinical outcome
Diagnostic Biomarkers
Find biomarkers from NGS data to classify patients and develop companion diagnostics
Next Gen Sequencing
Process fastq files from NGS to do alignment, count transcripts, call variants, and more
Predictive Biomarkers
Predict which patients are more likely to reach primary or secondary clinical endpoints
Generative AI
Use state-of-the-art generative AI models to predict molecular structures or binding
Causal Inference
Estimate causal effects from observational data using DAGs and modern inference techniques
Case Studies
We are a multi-disciplinary team focused on developing scientific insights using a mix of applied mathematics, machine learning, and computing.