SKU: 67458492575

Right Breast Replacement

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Description

Right Breast ReplacementBreast cancer is the second leading cause of cancer death among women; a properly performed manual examination is an important way of detecting cancer at an early, more treatable, stage. This Advanced Breast Exam Simulator offers unparalleled realism for teaching both clinical and self breast examination. Unlike other simulators, tissue density actually varies within the simulated breast, just as it does in a live patient. Tumors of varying sizes (1 4

Breast cancer is the second leading cause of cancer death among women; a properly performed manual examination is an important way of detecting cancer at an early, more treatable, stage. This Advanced Breast Exam Simulator offers unparalleled realism for teaching both clinical and self-breast examination. Unlike other simulators, tissue density actually varies within the simulated breast, just as it does in a live patient. Tumors of varying sizes (1-4 cm diameter), shapes (round, oval, irregular/stellate), and densities can be inserted by the instructor for an expanded combination of training scenarios. Tumors represent adenomas, cysts, malignant tumors, and enlarged lymph nodes. The torso is correctly positioned in the supine position and allows access to both axillae. The trainer features palpable ribs, sternum and clavicles, and enlarged lymph nodes in the axillary and subclavicular areas. Peau d’orange (“orange peel skin”) with inflammation, inverted nipple, skin dimpling, and asymmetry are also depicted on the incredibly realistic skin. The Advanced Breast Exam Simulator has been designed for supine examination, but may also be used standing upright if desired. Training may also be done without the overlay skin. Includes a rigid underbody, right and left breast inserts, overlay skin, three tumor sets (27 lumps), baby powder, hard carrying case, and instruction manual. Torso size: 14" W x 11" H x 6" D. Three-year warranty. This Model Simulator received top marks at a recent global health meeting. Healthcare professionals were elated with its realism, durability, materials and texture. Developed to assist Women and Health Professionals in teaching the processes and skills required to perform both: Self-examinations and Clinical Identification of pathologic Conditions. It is not possible to determine the exact nature of any tumor strictly by touch. Although many Breast Lumps are not cancerous, any Lump should be examined by a Health Professional. With Early detection - through Breast - Examination, clinical exams by a healthcare professional, mammography - the chances of surviving breast cancer increase dramatically. All women should perform monthly breast self- exam. Women after 40 and older should have a clinical breast exam every year.


Features
  • Teaching Clinical and self examination is made easy and realistic.
  • Tumors of varying sizes (1-4 cm diameter), shapes (round, oval, irregular/stellate), densities can be inserted
  • adenomas, cysts, malignant tumors, and enlarged lymph nodes.
  • positioned in the supine or standing upright position and allows access to both axillae.
  • features palpable ribs, sternum and clavicles, and enlarged lymph nodes in the axillary and subclavicular areas
  • orange peel skin”) with inflammation, inverted nipple, skin dimpling, asymmetry on skin
  • Training may also be done without the overlay skin
  • Torso size: 14" W x 11" H x 6" D.
  • Accessories
  • hard Carrying Case ---- Included
  • Three tumor sets (27 lumps)
  • Baby powder
  • Instruction Manual
Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
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Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 67458492575

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4.8 ★★★★★
Based on 16 reviews
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Verified Purchase
Shannon
Bozeman, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 30, 2025
W
Verified Purchase
William P Ross
Boise, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Louisville, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Houston, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Houston, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018

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