Relationship Graph Explorer
Follow the connections
Every herb, ingredient, formula, gene target, and disease — connected through real research. Search, pick a subject, and navigate the graph in any direction.
🌿
Herb
6,826
→
⚗️
Ingredient
45,885
→
🧬
Gene Target
15,695
→
🏥
Disease
30,467
→
🧪
Evidence
23,241
trials · metas · refs
Plus 6,743 TCM formulas connecting herbs together
16 Diseases matching "Cervical cancer"
Cervical Cancer
Cervical Cancer Metastasis
Cervix Carcinoma
Stage, Cervical Cancer
Stage Ib Cervical Cancer
Uterine Cervical Neoplasm
Stage Ib1 Cervical Cancer
Stage Iii Cervical Cancer
Stage Ia1 Cervical Cancer
Malignant Tumor of Cervix
Stage Iib Cervical Cancer Ajcc V8
Stage Iii Cervical Cancer Ajcc V8
Stage Ib1 Cervical Cancer Ajcc V8
Stage Ib Cervical Cancer Ajcc V6 And V7
Stage Iii Cervical Cancer Ajcc V6 And V7
Stage Iib Cervical Cancer Ajcc V6 And V7
🏥 Disease / Health Topic
Cervical Cancer
28
Clinical Trials
14
Meta-Analyses
0
PubMed References
📋 Sample Trials
NCT00365508
Counseling and Nicotine Replacement Therapy in Helping Adult Smokers Quit Smoking
Completed · Phase 4
NCT00790569
Varenicline or Nicotine Patch and Nicotine Gum in Helping Smokers in a Methadone Treatment Program Stop Smoking
Completed
NCT00002562
Paclitaxel in Treating Patients With Advanced, Refractory, or Recurrent Cervical or Vaginal Cancer
Completed · Phase 2
📊 Sample Meta-Analyses
CRD42016044030
The acceptance and effectiveness of a nurse-led visual inspection with acetic acid (VIA) screening programme for cervical cancer prevention for women in West Africa: a systematic review
The unsuccessful implementation of cytology-based screening tests for the preven
CRD42020206154
Systematic Review Evaluating the Effectiveness of Visual Inspection with Acetic Acid (VIA) as Compared to Primary HPV Testing and/or Pap Smear
This systematic review will focus on screening outcomes of Visual Inspection wit
CRD42021270745
Machine learning-based cervical cancer screening using cervigrams during visual inspection with acetic acid: a systematic review
Cervical cancer | Each year, around 266, 000 women die of cervical cancer and th
📚 Sample References
None linked yet.
🏥 All Disease / Health Topic data fields for Cervical Cancer
🏥 Names
Disease Name
Cervical Cancer
Alias Names
Cervical Cancer; Uterine Cervical Neoplasms; Uterine Cervical Neoplasm; Cervix Cancer
Topic Type
disease
🧬 Ontology Classifications
DisGeNET Type
disease
UMLS Type
Neoplastic Process
MeSH Class
Female Urogenital Diseases and Pregnancy Complications; Neoplasms
HPO Class
Neoplasm; Abnormality of the genitourinary system
DO Class
disease of anatomical entity; disease of cellular proliferation
🔗 External References
🔍 Raw view — every non-empty column on this row (31 fields)
name
Cervical Cancer
alias name
Cervical Cancer; Uterine Cervical Neoplasms; Uterine Cervical Neoplasm; Cervix Cancer
topic type
disease
disgenet disease type
disease
umls disease type
Neoplastic Process
mesh disease class
Female Urogenital Diseases and Pregnancy Complications; Neoplasms
hpo disease class
Neoplasm; Abnormality of the genitourinary system
do disease class
disease of anatomical entity; disease of cellular proliferation
umls disease type id
T191
mesh disease class id
C04; C13
hpo disease class id
HP:0000119; HP:0002664
do disease class id
DOID:14566; DOID:7
herb disease id
HBDIS025310
disgenet id
C4048328
mesh id
D002583
hpo id
HP:0030079
do id
4362
omim id
603956
tcmsp disease id
158
🧬 Gene / Protein Targets
1 · genes implicated in this diseaseALOX5
Gene ALOX5
How to read these connections
Each box lists records connected to the one you are viewing, and says how the connection was made. A connection shows that two records are related in the source data. It does not show that something works, is safe or should be used, and a record with many connections is not necessarily better studied or more effective.
- Study records (trials, systematic reviews, publications): the study names this subject. Registered or ongoing studies have no results here, and animal or cell research does not show an effect in people.
- Source-database links (for example herb and compound, compound and gene target): taken from the imported databases and not independently checked by us.
- Name matches (for example formula and herb, or a condition named in a study): found by matching names, so they can be wrong. Treat them as leads, not findings.