Abstract: Systems and methods are described for obtaining an additive AI result from a digital file, the method including: processing the digital file by at least one first artificial intelligence (AI) classifier and at least one second AI classifier thereby obtaining a first evaluation result and at least one second evaluation result respectively; directing the first evaluation result and the at least one second evaluation result to at least one synthesis processor; and comparing the first evaluation result and the at least one second evaluation result to at least one dataset cluster thereby obtaining the additive AI result.

Abstract: Systems and methods are described for obtaining an additive AI result from a digital file, the method including: processing the digital file by at least one first artificial intelligence (AI) classifier and at least one second AI classifier thereby obtaining a first evaluation result and at least one second evaluation result respectively; directing the first evaluation result and the at least one second evaluation result to at least one synthesis processor; and comparing the first evaluation result and the at least one second evaluation result to at least one dataset cluster thereby obtaining the additive AI result.

Abstract: Systems and methods are described for obtaining an additive AI result from a digital file, the method including: processing the digital file by at least one first artificial intelligence (AI) classifier and at least one second AI classifier thereby obtaining a first evaluation result and at least one second evaluation result respectively; directing the first evaluation result and the at least one second evaluation result to at least one synthesis processor; and comparing the first evaluation result and the at least one second evaluation result to at least one dataset cluster thereby obtaining the additive AI result.

Abstract: Systems and methods are provided herein for training at least one Artificial Intelligence (AI) processor, the method including: evaluating a digital data signal by the at least one AI processor to obtain an evaluation data point; comparing and transforming the evaluation data point by the AI processor to at least one designated data point thereby obtaining a transformed evaluation data point; analyzing and matching the evaluation data point or the transformed evaluation data point by the AI processor to the at least one designated data point; and presenting the transformed evaluation data point to the AI processor thereby training the AI processor.

Abstract: System and methods are provided for building and training an Artificial Intelligence (AI) classifier for detecting an indicium of a: disease, condition, and a feature in a digital file by: assembling a positive data set and obtaining positive evaluation results by processing the positive data set by the AI classifier with or without other medical data thereby training the AI classifier for positive data; assembling a negative data set and obtaining negative evaluation results by processing the negative data set by the AI classifier with or without other medical data thereby training the AI classifier for negative data; analyzing a test data set by the AI classifier to obtain test evaluation results and sorting the test evaluation results by a probability threshold to obtain sorted results; and examining the sorted results to identify incorrectly sorted results and retraining by reanalyzing the AI classifier for the incorrectly sorted results.