Tagged medical

Classify clinical trial protocol deviations as major or minor under ICH E6 GCP

Read, write and anonymize DICOM medical images and extract their pixel data

Build clinical prediction models on EHR data with MIMIC, eICU and OMOP datasets

Map patient symptoms to Human Phenotype Ontology terms for rare disease diagnosis

Design real-world evidence studies from EHR, claims or registry data

Write clinical referral letters with patient summary, findings and next steps

Plan sample size, power assumptions and fallback enrollment for clinical protocols

Summarize EHR records into shift handovers with critical events and pending tasks

Write GCP-compliant SOPs with roles, steps and control points for lab or clinical work

Identify the real design of a medical paper and its evidence level

Generate Table 1 baseline characteristics for clinical research papers

Convert medical text between academic and patient-friendly reading levels

Assess clinical trial feasibility with population sizing, endpoints and regulatory paths

Match patient profiles to ranked ClinicalTrials.gov trials by molecular eligibility

Map research streams, populations, endpoints and thin areas for a medical topic

Write concise patient treatment plans with SMART goals, monitoring and PDF output

Plan studies that predict treatment response or drug resistance in clinical research

Run univariate and multivariable Cox models on clinical survival data with forest plots

Extract specific unmet clinical needs from guidelines, reviews and real-world studies

Mine clinical notes from MIMIC-IV to extract diagnostic reasoning patterns

Generate USMLE Step 1 and Step 2 style clinical cases for exam practice

Design internal, external, temporal and functional validation plans for medical studies

Practice OSCE history-taking with a simulated standardized patient and get feedback

Write detailed text descriptions of medical images and charts for readers

Set disease pathways, endpoints and treatment timelines for clinical imaging studies

Design clinical use, reader impact studies and deployment evidence for imaging AI

Convert clinical lab values between US and SI units and clean data quality issues

Interpret somatic cancer mutations with CIViC and OncoKB evidence and therapy options

Review drug safety end to end from FDA labels, FAERS reports and trial data

Search NICE, WHO, NCCN and other clinical practice guidelines for treatment advice

Calculate bedside clinical risk scores such as CHA2DS2-VASc for one patient

Normalize drug and condition names to RxCUI and ICD-10-CM codes

Assess trial design feasibility, endpoints, population and regulatory path

Match patient molecular profiles to ranked oncology clinical trials

Draft a full clinical trial protocol that follows ICH E6 and FDA style

Trace how a drug acts from primary target to pathway and clinical effect

Rank CRISPR and shRNA screen hits by essentiality, druggability and clinical evidence

Browse TCIA cancer imaging collections and DICOM series by patient and modality

Split patients into responder groups and risk tiers from genomic and clinical data

Rank rare disease diagnoses from patient phenotypes using HPO terms

Talk with youth in a patient and supportive way

Design adaptive clinical trials with group-sequential bounds and sample-size re-estimation

Design Bayesian clinical trials with dose-finding, priors and platform designs

Test categorical clinical outcomes with chi-square, Fisher and McNemar tests

Validate and prepare CDISC SDTM and ADaM clinical trial datasets for analysis

Compute odds ratios, risk ratios, hazard ratios and NNT with calibrated intervals

Run logistic regression for trial outcomes with marginal effects and Firth fits

Run missing-data sensitivity analyses for confirmatory trials with MMRM and imputation

Control multiplicity in trials with graphical procedures, gatekeeping and closed testing