Upload X-rays, CT, MRI and gene expression data. Get publication-grade gene–feature correlations, volcano plots, Kaplan–Meier survival curves, unsupervised phenotype clustering, AI-written insight reports and cross-study meta-analysis — all tied to the studies your lab is running.
3-day free trial · 4 scans · full analysis-module access (except sharing) · no card required. Paid plans from $ 100/mo.
Cohort insight preview
Pathway: Innate immunity · TLR signaling
Everything in one platform
Every analysis is bound to a Study/Project. Upload once — get correlations, pathway enrichment, survival curves, clusters and an AI insight report in the same workspace.
Upload chest X-rays, CTs or MRIs and run single-scan AI classification with GPT-5.2 Vision — clinically-framed prognosis output plus DICOM support.
Choose your track at study creation. Paired (imaging + gene expression from the SAME patients) unlocks individual-level association testing; External (independent public transcriptomic datasets) runs cohort-level, hypothesis-generating analysis — each with the correct scientific guardrails and report labels.
Upload a subjects×genes matrix and compute true cross-cohort correlations against radiomic features — Spearman (default) or Pearson, with Benjamini-Hochberg FDR across all pairs, gene-symbol standardization, QC and paired subject-ID validation.
Per-subject pathway activity scores (z-scored gene signatures across 8 curated pathways) correlated with radiomic features — more biologically meaningful than single-gene results, FDR-corrected.
Split the cohort by a radiomic feature (median/tertile) or diagnosis and find differentially-expressed genes — log₂FC, Mann–Whitney U, FDR, plus a volcano plot and top up/down tables.
Every gene-feature pair plotted as r vs −log₁₀(p). Filter by significance, |r| threshold or pathway, then click any point to drill into GeneCards and Reactome.
Hypergeometric over-representation with Benjamini-Hochberg FDR on built-in panels — see which pathways the significant correlations cluster into.
Upload subject survival CSVs, stratify by any gene or radiomic feature for Kaplan–Meier + log-rank, and fit real Cox proportional-hazards models (radiomic/gene/pathway predictors) with hazard ratios, 95% CI, FDR and concordance index.
KMeans + PCA on z-scored radiomic + gene matrix reveals subject subtypes with per-cluster top discriminating features and silhouette quality.
Compare two scans — or two subject groups — side by side, with per-feature deltas and group-vs-group significance.
Build correlation-driven gene co-expression networks with edge thresholding and hub-gene detection, plus differential co-expression across cohorts.
Map your significant genes onto STRING-DB protein interaction networks to expose functional modules and candidate driver proteins.
Track B: map each imaging phenotype group to the most biologically-consistent external transcriptomic signature (with confidence tiers) — cohort-level, hypothesis-generating, never patient-level.
Test whether a query signature replicates across multiple independent public datasets — per-dataset significance plus a strong/moderate/weak/not-replicated verdict.
Pool gene-feature correlations across studies via Fisher's z-transform with Cochran's Q + I² heterogeneity. Ready for supplementary methods.
A senior-analyst-style markdown report synthesizes correlations, survival and clusters into Key Findings, Pathway Patterns and follow-up hypotheses.
Ask questions about your studies in plain language — GPT-5.5 for fast Q&A and Claude Sonnet 4.6 for manuscript-grade writing, grounded in your cohort data.
Record or upload a cough, add a WHO-style symptom screen, and get an explainable AI pre-screening estimate (elevated / low / inconclusive) from real acoustic features. Link it to a scan's subject and it feeds the AI manuscript. Research/pre-screening only — not a diagnosis.
Invite collaborators to any study to co-edit, run analyses together and review results in one shared workspace — leave or unshare anytime.
Track-aware reports (Paired Radiogenomics vs External Radiotranscriptomics) with AI executive summary, suggested manuscript titles, mandated safety statements, and one report exported as CSV/JSON/PDF/DOCX — plus read-only share links and GeneCards/Reactome deep links throughout.
Simple, transparent pricing
Pay monthly in USD via PayPal. Cancel any time.
4 scans / trial
50 scans / month
Unlimited scans
Unlimited usage within paid modules · pay only for what you need
All plans are billed in USD via PayPal. Need a Lab/Institution plan with 10+ seats? Contact us.
Loved by researchers
Researchers highlight RespiraDiagnose for its impressive accuracy in prognosis classification and the valuable insights it provides into the biological associations of radiomic features. With its user-friendly interface and affordable pay-per-module subscription, it has proven to be a vital tool for data analysis and publishing impactful research in the field.
AI-summarized from verified researcher reviews
“I published my paper "Artificial Intelligence-Driven Prognostic Classification of COVID-19 Using Chest X-rays: A Deep Learning Approach" and compared my results using Microsoft CustomVision with the results from RespiraDiagnose - accurate and much better in terms of the details of prognosis. I like the Gene Network and Protein network interactions.”
Alfred Simbun
Researcher · MSU Shah Alam
“I published my paper "Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network" few years ago and stumbled upon RespiraDiagnose. It gave me the same accuracy of prognosis classification. Kudos!”
Asmaa Abbas
Researcher
“I really think that RespiraDiagnose has helped me to understand the biological association with every individual radiomic features of my xray images.”
Zahid
Researcher · UiTM Shah Alam
“I used this to scan my xray images two years ago and I saw so many new things being offered by this portal with affordable pay-per-module subscription package. It really helped me to analyze my data and publish my first paper.”
Isaac
Researcher · Management & Science University (MSU) Shah Alam
Start with the 3-day free trial. No credit card. Four scans and full analysis-module access — cohort correlations, survival, gene networks and more. Upgrade in one click when your trial ends.
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