ResearchRabbit

At a glance

Pricing

Free.

HIPAA

Not disclosed

SOC 2

Not disclosed

EHRs

—

Founded

—

Bottom line

Visual citation-network mapping ("Spotify for papers").

Free tier available.

Overview

Pricing

What it costs

Free tier only; no paid plans publicly disclosed.

Source: vendor pricing page. Verified May 23, 2026.

Peer-reviewed coverage

What the literature says

5 peer-reviewed studies indexed on PubMed evaluate ResearchRabbit in clinical contexts. The most relevant are shown below, ranked by editorial relevance score combining title match, study design, recency, and journal tier.

The association between thyroid disease and hearing loss: a meta-analysis.

Gu L, Guo W, Wang X, et al.· Acta Otolaryngol· 2024Meta-Analysis

It has been shown that there is a link between thyroid-related diseases and hearing loss. The purpose of this study is to investigate the relationship between thyroid-related diseases and hearing loss by conducting a meta-analysis. A thorough search was carried out in the following electronic databases: PubMed, Cochrane Library, Embase, Web of Science, Google Scholar, Semantic Scholar, and ResearchRabbit. The chi-square test and theindex examined the research's heterogeneity. A funnel plot and the Eger test were used to examine publication-biased effects. A total of 48,507 individuals (6482 h…

Cancer stem cells and post-therapy tumour recurrence: a systematic review of mechanistic pathways and translational gaps.

Barjij I, Meliani M· Ecancermedicalscience· 2025Systematic Review

Cancer stem cells (CSCs) are increasingly recognised as pivotal drivers of tumour recurrence and treatment resistance across multiple malignancies. Despite extensive preclinical investigations, the mechanisms by which CSCs mediate relapse after therapy remain insufficiently integrated and poorly translated into clinical frameworks. This systematic review aimed to synthesise current mechanistic evidence linking CSC biology to post-therapeutic recurrence in solid and hematologic tumours, highlighting recurrent molecular pathways, experimental models and translational gaps. Following Preferred R…

Multifaceted and educational interventions to improve prescribing indicators in the Middle East and North Africa Region: a systematic review and meta-analysis.

Ilyas M, Chivese T, Hadi MA, et al.· Int J Clin Pharm· 2026Meta-Analysis

Rational prescribing is challenging due to global antibiotic resistance and widespread polypharmacy. Evidence on effective interventions to improve prescribing practices in MENA is limited. This systematic review and meta-analysis evaluated the effectiveness of multifaceted and educational interventions in improving WHO/INRUD prescribing indicators in the Middle East and North Africa (MENA). We searched PubMed, Scopus, and CINHAL up to June 10, 2025, for experimental studies evaluating the effectiveness of multifaceted interventions on WHO/INRUD prescribing indicators. Searches were supplemen…

Artificial Intelligence Tools in Biomedical Research: Part 1-Literature Search and Knowledge Mining.

Sen CK· Antioxid Redox Signal· 2026Editorial

The exponential growth of biomedical literature has rendered traditional search methods inadequate. Artificial intelligence (AI) tools have emerged and are developing as transformative solutions for literature search and knowledge mining. This first article of a series, intended to address different components of biomedical research, provides a comprehensive analysis of recent advancements, practical applications, and challenges in deploying AI for biomedical research. The objective of this work is to synthesize the evolution, capabilities, and limitations of AI-driven tools for literature di…

Machine Learning Models for Predicting Radiation Dermatitis in Breast Cancer: A Scoping Review.

Meneses JCBC, Santos Neto ATD, Domingos MAF, et al.· Comput Inform Nurs· 2026

Artificial intelligence, particularly machine learning, has great potential to improve health outcomes, including predicting adverse conditions. In breast cancer, machine learning models can help personalize prevention strategies for radiation-induced cutaneous toxicity. This scoping review aimed to explore machine learning models for predicting radiation dermatitis in women with breast cancer. Data collection was conducted in November 2023 from 7 electronic databases and gray literature, with no restrictions on publication year. Publication selection was supported by the RAYYAN reference man…

See all on PubMed