I am planning to develop an AI for the healthcare industry that could help improve professionals' decisions in giving accurate diagnoses and prognosis for their patients. There will be a series of models that will be integrated to this system. On the first part, I want that the system will predict if the patient depending on the input (which would be the images of lab test results, and or manual entry of text data) has a high chance of having diabetes, kidney disease, and cardiovascular disease. It will summarize and analyze the dataset to solve for the probabilities of certain diseases. Displ ..read more

How would I go about implementing a mobile app that uses a machine learning algorithm on the backend to track a certain metric for the users? Assuming that the server is already set up and the algorithm is loaded and ready to receive data, all I want to do is send the data from the mobile app (maybe in a JSON format) to the server, perform inference on it, produce a calculation for the target variable, and then adjust a value that is tracked in the user’s information back on the phone. So what would be a good way to go about this? Apologies if the question is amateurish but I’m not familiar wi ..read more

In the context of developing an AI-powered application for analyzing and mitigating reputational risks in social media statements, what are the most effective natural language processing techniques for detecting potentially offensive or culturally insensitive content ..read more

Not sure whether this is a fitting place to ask such a question, but here goes... I learned about simple machine learning and supervised/unsupervised training back in Uni, where I specialized in machine learning, but haven't been able to utilize/practice that in my day-to-day work - which I am trying to do now. What I seem to struggle with is understanding how one is supposed to work iteratively/logically when training a model and trying to apply it. Today I tried to train an object detection model which couldn't detect anything and had 0% accuracy after a day of labeling data and an hour of m ..read more

Closed. This question is opinion-based. It is not currently accepting answers. Update the question so it can be answered with facts and citations. This will help others answer the question. You can edit the question or post a new one. Closed 5 hours ago. I am working on a project that involves integrating various types of IoT sensors, which require periodic calibration and adjustment with a correction factor. As the network of these sensors expands, there is a need to implement network-level correction. This involves calibrating multiple sensors in relation to each other, with some sensors fun ..read more

I haven't found resources from people working on object recognition of 3d cad models. I'll pose a problem I'd like to be able to solve: I have a library of cad models containing thousands of combustion engines. I need a program that can recognize where the crank shaft axis is in 3d space. I think a convolutional neural network could be programed to recognize 3d solids. By turning a cad model into a voxelated version of the part, you could slice the data and present the data similarly to 2d images. Though, I'm not sure how you could convolute a zero-thickness mathematical construct such as an a ..read more

I'm a passionate third-year Computer Engineering student, and I'm reaching out in pursuit of valuable advice. Lately, I've noticed that most of my peers have made remarkable strides in machine learning, natural language processing (NLP), and deep learning. Their expertise is truly inspiring, and it has ignited a strong desire within me to not only catch up but also excel in these fields. However, I must admit that there are times when I feel overwhelmed by the sheer complexity and vastness of machine learning and NLP. The rapid pace of advancement and the depth of knowledge required can be dau ..read more

From this research paper I want to write an algorithm for finding envy-freeness(EF) and Pareto optimality(PO) division for more than two agents. We consider the problem of fairly and efficiently allocating indivisible items (goods or bads) under capacity constraints. In this setting, we are given a set of categorized items. Each category has a capacity constraint (the same for all agents), that is an upper bound on the number of items an agent can receive from each category. Our main result is a polynomial-time algorithm that solves the problem for two agents with additive utilities over the i ..read more

The model I'm building first selects a secret word at random from a list. The model which uses an API then returns a row of underscores (space separated)—one for each letter in the secret word—and asks the user to guess a letter. If the user guesses a letter that is in the word, the word is redisplayed with all instances of that letter shown in the correct positions, along with any letters correctly guessed on previous turns. If the letter does not appear in the word, the user is charged with an incorrect guess. The user keeps guessing letters until either (1) the user has correctly guessed al ..read more

I had an idea where I want to train a model based on two other neural networks (nn). These two NN share the same objective goal, but have differing levels of performance, for ht objective task, as they are trained on different domains. Is there any precedent for a model where competitively train the two models against each other, and combine the best of both results adversarially? Is there precedent on this type of machine learning model ..read more