Research translated into real-world clinical capability

Making complex health data clinically useful.

Consultitnow works at the intersection of machine learning, biomedical signal processing and medical imaging—turning physiological and imaging data into interpretable decision support for clinicians, researchers and healthcare innovators.

Explore selected work View profile

5featured programmes

3clinical domains

2delivered products

Multimodal health intelligenceLIVE

EEGMRIPETCOGNITIONIMAGING

ExplainableEvidence clinicians can interrogate

DeployableFrom research to working products

01 / PROFILE

Clinical impact demands more than a high-performing model.

Consultitnow connects research expertise with applied product development across neurology, gastroenterology and musculoskeletal diagnostics. Every engagement is shaped by explainability, diagnostic accuracy and real-world deployability.

Software publishing Digital health platforms and decision-support products
IT consultancy AI strategy, data science and technical delivery
Technology services Research translation, prototyping and deployment

02 / SELECTED WORK

Five representative projects

Research depth. Product delivery. Hospital relevance.

Research

CLEAR-AD

Explainable causal AI for early Alzheimer's risk assessment and personalised disease modelling.

Technical approach

Longitudinal MRI, PET, cerebrospinal fluid biomarkers and cognitive assessments are integrated into a multimodal causal pipeline, with personalised counterfactual simulations of patient trajectories.

Clinical relevance

Designed to support earlier diagnosis, disease staging, risk stratification, clinical trial recruitment and explainable multidisciplinary case review.

Product

AI-Assisted Gastroenterology Imaging Platform

Real-time endoscopic decision support delivered as a cloud-based clinical product.

Technical approach

Computer vision and content-based image retrieval match live endoscopic images to a validated library, returning visually similar cases with biopsy-confirmed diagnoses.

Clinical relevance

Supports screening consistency, reduces unnecessary biopsies and provides a structured training environment for junior clinicians.

Product

NEVE

AI-powered neurohealth platform combining wearable EEG, cognitive testing and cloud analytics.

Technical approach

Multimodal biomarkers from EEG and behavioural performance generate personalised, longitudinal measures through secure cloud infrastructure and explainable analytics.

Clinical relevance

Enables non-invasive monitoring between visits and offers clinician-facing cohort and case-level analytics through NEVE Pro.

Research

MCI Detection via EEG Self-Supervised Learning

Data-efficient early detection of Mild Cognitive Impairment from EEG signals.

Technical approach

Temporal, spectral and functional-connectivity features are combined with contrastive self-supervised representation learning and anomaly detection.

Clinical relevance

Supports scalable, non-invasive screening where labelled clinical data is limited, including primary-care pathways ahead of specialist referral.

Animated EEG and neural connectivity analytics dashboard

Research

CADOS

Computer-Assisted Diagnosis of Osteoporosis from conventional X-ray images.

Technical approach

Region-of-interest segmentation, multiresolution texture analysis, explainable deep learning and case retrieval assess bone microarchitecture.

Clinical relevance

Offers scalable screening using widely available radiography, with visual evidence and similar-case retrieval supporting radiologist review.

03 / CAPABILITIES

Core expertise

Built for multidisciplinary healthcare AI programmes.

Biomedical signal processing

EEG pipelines, temporal and spectral features, functional connectivity and digital biomarkers.

Medical imaging AI

Segmentation, classification, texture analysis, retrieval and interpretable diagnostic support.

Explainable & causal AI

Models that expose evidence, causal structure and counterfactual scenarios rather than opaque scores alone.

Clinical product translation

Secure cloud analytics, clinician dashboards, annotation workflows and deployable decision-support products.

A consistent delivery philosophy

Accurate enough for research. Clear enough for clinical review. Practical enough to deploy.

01Explainability is designed in—not added after model development.

02Validation is connected to the clinical question and operational pathway.

03Interfaces translate complex signals into useful evidence and action.

AI consultancy · Research · Product collaboration

Turn a healthcare AI opportunity into a credible programme of work.

Consultitnow supports clinical AI research, grant collaboration, technical advisory, product strategy and translational development.