4.8
4,995 条评分
★★★★★
2026年2月23日
2017年2月23日
更新内容
v1.9Various bug fixes and performance improvements.
应用信息
- 开发者
- AMBOSS
- 分类
- Medical
- 价格
- 免费
- 版本
- 1.9
- App ID
- 1169403493
简介
The AMBOSS Qbank App for USMLE® Step, NBME® Shelf, NBOME® COMLEX-USA, ABIM, ABFM, ABP exams is the ultimate test preparation and study resource for medical students and residents. Dive into thousands of questions to enhance your knowledge and prepare for all of your exams. The AMBOSS Qbank App will rigorously prepare you for the USMLE Step 1, Step 2 CK, Step 2 CS, Step 3, NBME Subject Board (Shelf) exams, and your clerkships, COMLEX Level 1, Level 2-CE, Level 3 and COMAT — Osteopathic principles and practice along with NEJM Knowledge+ questions for ABIM, ABFM, and ABP Board Review. AMBOSS Qbank App works online and offline, so you can answer questions and reinforce your knowledge anytime, anywhere. It’s cross-linked with the AMBOSS Knowledge App so you can practice questions in the Qbank while simultaneously looking up relevant terms in the AMBOSS Knowledge Library. AMBOSS Knowledge and AMBOSS Qbank Apps combine to give you one powerful exam-preparation resource. With AMBOSS Qbank App, you can: Stay on track: Use Study Mode to guide your learning process. The Key Info and Attending Tip are tools that will help you with challenging questions and nudge you in the right direction when needed. Bridge any knowledge gaps: After a Qbank session, you’ll get a personal analysis and study recommendations that will show you the areas you need to focus on the most. Perform under pressure: Test yourself with Exam-Mode and be prepared for USMLE and Shelf exam conditions. Get more than questions: Dive into interactive image overlays and flowcharts to improve your learning, study smarter, and score higher. Additionally, the cross-linked AMBOSS Knowledge App will give you easy access to the right information. Download the app today! Terms and Conditions: https://www.amboss.com/us/terms Privacy Policy: https://www.amboss.com/us/privacy
下载量预测
预估总下载量
2K
低 / 月
3K
预估 / 月
6K
高 / 月
基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。
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