Python Abdominal X-Ray Classifier

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@nrajuu07

As a data scientist who has showcased expertise in deep learning and machine learning for a variety of medical imaging tasks, I am the perfect choice for your Python Abdominal X-Ray Classifier project. With hands-on experience in handling large datasets, selecting optimal models, feature engineering, and hyper-parameter tuning, I've consistently achieved high accuracy rates. My previous work with radiology datasets will certainly be beneficial in understanding and addressing the specific nuances that come with analyzing X-ray images.

@lalitdeveloper7

Hi I can develop a robust deep-learning pipeline to classify abdominal X-ray images with a focus on achieving high accuracy on unseen validation data, handling data preparation, augmentation, model training, tuning, and evaluation using a mainstream framework like PyTorch or TensorFlow. The solution will be modular, well-documented, and production-ready, with trained weights, clear metrics, and a concise report explaining design choices and results. Please let me know further. Thanks

@rakam26

Hello Just read your post and it seems you are looking for a deep learning engineer skilled in medical image classification and computer vision. With my years of extensive experience and exceptional expertise in Python, PyTorch/TensorFlow, medical imaging pipelines, data augmentation, and CNN-based model optimization, I am 100% confident that I can bring your abdominal X-ray classification project to life in the shortest possible time. I’ve delivered high-accuracy (>90%) models on radiology-style datasets before, including end-to-end workflows covering preprocessing, architecture selection (ResNet/EfficientNet), hyperparameter tuning, and clean, modular code for future retraining. Let’s connect and see how great value I can add to your business. Best Regards Raka

@ABDOKAMA

Hi, I am an experienced AI Developer and former Backend Team Leader. I specialize in Computer Vision and have handled massive radiology-like datasets involving complex feature extraction. I can deliver the Python scripts, trained weights, and performance report you need with >90% accuracy. I am so confident in my results that I am happy to start with a test phase to prove my model's performance on your validation set. Looking forward to working with you!

@yacinebsd

I have experience working on medical imaging projects, including abdominal X-ray classification and keypoint detection for the legs and spine. In that project, I built a robust Python pipeline that handled data augmentation, trained deep-learning models, and accurately detected anatomical landmarks alongside clinical findings. For your project, I can leverage that experience to deliver a production-ready solution that achieves high accuracy, with modular code, trained weights, and a clear README for retraining or fine-tuning. I’m happy to discuss the approach in detail or run a small demo on sample images before full implementation.

@msaadarshadkhan

Hi there, I am ready to start Python Abdominal X-Ray Classifier . Last time, I did the same project by just… doing the work. No corporate theater, no 47 meetings about meetings. I’m annoyingly good at details, I hate wasting time, and I actually want to build something here,,not just collect a paycheck. You can check similar projects here: https://www.freelancer.com/u/msaadarshadkhan If you’re tired of cover letters that feel like Mad Libs, hit reply. Coffee’s on me.

@christianw71

Hello, With my extensive eight-plus years of experience working as a Senior Full-Stack Developer in both JavaScript and Python ecosystems, I am an ideal candidate for your Python Abdominal X-Ray Classifier project. Throughout my career, I've been committed to delivering high-quality, well-documented code - and that is precisely what you can expect from me. My ability to build scalable APIs and backend systems aligns perfectly with the requirements of your project. When it comes to selecting mainstream frameworks like TensorFlow, Keras, or PyTorch, I'm well-versed in each one of them. Additionally, my familiarity with data preparation and augmentation, model architecture selection, training, hyper-parameter tuning and evaluation ensures a comprehensive approach to the project. Importantly, I've previously worked on medical imaging projects involving radiology datasets where I achieved high accuracy levels much like the target you've set. Beyond just delivering the project requirements with >90% accuracy on your dataset's hold-out set, I will also provide a concise report that explains all the decisions made, metrics used and any suggestions for future improvements. This report will not only help you understand the classifier better but will act as a reference document for retraining or fine-tuning in the future as new data gets added. Trust your project to me, a highly skilled professional who is committed to delivering powerful Thanks!

@ShaydeeN1

I am a perfect fit for your project that requires a clean, professional, and user-friendly deep-learning pipeline for abdominal X-ray classification with over 90% accuracy. Your need for modular, well-commented Python code that supports seamless retraining and fine-tuning aligns perfectly with my approach. While I am new to freelancer, I have tons of experience in medical imaging and computer vision, working extensively with TensorFlow and PyTorch on robust data augmentation, architecture tuning, and performance evaluation. I would love to chat more about your project! Regards, Shay-Dee

@mudassarmehdi99

Hi, I understand the challenge of building a reliable X-ray classifier. Low accuracy or poorly structured code makes retraining difficult and slows deployment. You need a robust Python solution that achieves >90% accuracy while remaining modular for future updates. I can develop a production-ready model using TensorFlow, Keras, or PyTorch—handling data preparation, augmentation, model design, training, hyperparameter tuning, and evaluation. The code will be clean, well-commented, and easily adjustable for new data. I’ll also provide trained weights, inference scripts, and a concise report summarizing performance and future improvement suggestions. To make sure I deliver exactly what you need: 1. Are there specific clinical findings or classes to prioritize in the classifier? 2. Do you prefer a particular framework (TensorFlow, Keras, PyTorch) for production compatibility? 3. Should the model include automated preprocessing pipelines for incoming images? 4. Is GPU training available, or should the code be optimized for CPU? Looking forward to your reply so we can start building a high-accuracy, production-ready X-ray classifier quickly. Best regards, Mudassar M.

@ammaramajeed1994

Hello, Yes, I can manage this project end to end. I have already worked on similar deep-learning image classification tasks and I’m comfortable handling the complete pipeline independently. I will take care of data preparation and augmentation, model selection, training, hyper-parameter tuning, and evaluation on an unseen validation set. I will deliver clean, modular, and well-commented Python code, trained model weights/checkpoints, a clear README for setup and inference, and a brief performance report confirming the achieved accuracy. Once you share the sample images, I can quickly review the dataset and finalize the approach so we can move forward without delay. Looking forward to working with you. Best regards, Ammara

@jibrank00

Hello, I have aggressive experience building deep-learning models for medical imaging, specializing in radiology datasets and high-accuracy classification tasks. My tech stack includes Python, PyTorch, TensorFlow, and Keras, with modular pipelines for data augmentation, hyperparameter tuning, and production-ready deployment. I ensure models are explainable, maintainable, and easily fine-tunable with new data. For your dataset, are there specific clinical findings you want prioritized, and how many classes should the model distinguish? Lets do start right now jump in chat and get started? Best, JIbran

@mrmushtaque

I have hands-on experience building computer-vision classifiers with transfer learning, data augmentation, and rigorous evaluation pipelines. I focus on reproducibility (fixed seeds, versioned checkpoints), careful metric tracking, and practical deployment considerations (model export, batch inference). For medical imaging, I use conservative, domain-appropriate augmentations and class-imbalance handling to improve generalization and reduce overfitting. I will work iteratively with you to reach the target performance and document how to extend the model as more data arrives.

@selcuk6

Hi, I am an expert in Python and Web Scraping. I can build this automation tool for you quickly. Ready to start. I have extensive experience in medical imaging classification and deep learning. I have worked with TensorFlow and PyTorch for radiological image Analysis and can reach high accuracy using transfer learning and custom data augmentation techniques.

@MariamQadeem

Hello sir ! I can build a Python deep-learning model for your abdominal X-rays. I will prepare the data, train the model, and get >90% accuracy. I can deliver clean code, trained weights, and a short report. I will make sure the code is easy to retrain and understand. I am ready to start and deliver a production-ready solution.

@hassam945

Hi there, Building a top-notch Python abdominal X-ray classifier requires a combination of robust AI and ML skills, precisely the ones I hold. My in-depth experience in computer vision and medical imaging makes me the perfect fit for this task. Over the years, I have designed intelligent systems capable of high diagnostic accuracy, similar to what you need. My profound understanding of supervised and unsupervised learning coupled with strong expertise in mainstream frameworks like Tensorflow will ensure a comprehensive and effective solution. With every project I undertake, I prioritize efficiency, scalability, and real-world readiness; your project will be no different. I will handle all aspects, starting from data preparation and augmentation to architecture selection, model training, hyper-parameter tuning for optimal performance and evaluation that guarantees superior results on unseen validation sets. Moreover, my skill set also includes Flask and REST APIs which enable me to develop deployment-ready code with clear instructions for future use. Lastly, as an expert in delivering concise reports that not only explain my approach but also suggest areas for continued improvement, you can rely on me to provide a complete package that fulfills all your requirements. Hire me now and let's turn this project into a success!

@akshatt69

With an extensive background in developing robust AI and ML solutions, I am confident that I'm the best fit for your Python Abdominal X-ray Classifier project. My proficiency spans across multiple mainstream frameworks such as TensorFlow, Keras, and PyTorch, which aligns perfectly with your preference of using any of them. Furthermore, my strong command of the whole pipeline is an added asset which you will greatly benefit from. Not only can I deftly handle preparation, augmentation of data, but also excel in model architecture selection, training, hyper-parameter tuning, and evaluation--all skills demanded by this particular project in order to ensure consistent and reliable accuracy over 90%. Moreover , my career has seen me tackle a wide range of tasks including those involving medical imaging or computer vision. This includes tasks that demanded high accuracy on radiology datasets or required working with domain-specific augmentations; experiences that will resonate well with your unique project requirements

@AhmedAlhour

Hello, I’m very interested in building your abdominal X-ray classification model. I have hands-on experience developing deep-learning models for medical imaging with a strong focus on high validation accuracy and reproducibility. Relevant Experience • Trained CNN/transfer-learning models (ResNet, EfficientNet, DenseNet) on radiology datasets • Achieved >90% validation accuracy on multi-class X-ray classification tasks • Applied medical-specific preprocessing (normalization, CLAHE) and controlled augmentations • Built full pipelines: data prep → augmentation → training → tuning → evaluation • Delivered modular, well-commented PyTorch/TensorFlow code with checkpoints Approach Use PyTorch (preferred) or TensorFlow Transfer learning with EfficientNet/ResNet backbone Stratified split + proper hold-out validation Hyperparameter tuning (LR scheduling, regularization) Metrics: accuracy, sensitivity, specificity, confusion matrix Deliverables ✔ Clean Python source code ✔ Trained weights/checkpoint ✔ README with setup & inference steps ✔ Brief report confirming >90% accuracy on your hold-out set