ascopubs.org

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia

A total of 737 treatment-naïve patients with CLL diagnosed at Mayo Clinic were included in this study. We compared predictive abilities for two survival models (Cox proportional hazards and random ...
InfoWorld

Unsupervised learning explained

Unsupervised learning is used mainly to discover patterns and detect outliers in data today, but could lead to general-purpose AI tomorrow Despite the success of supervised machine learning and deep ...
Seeking Alpha

WiMi Launches Quantum-Assisted Unsupervised Data Clustering Technology Based on Neural Networks

BEIJING, Oct. 1, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the launch of a ...
PBS

Unsupervised Learning #6

We’re moving on from artificial intelligence that needs training labels. We’re moving on from artificial intelligence that needs training labels, called Supervised Learning, to Unsupervised Learning ...
Seeking Alpha

MicroCloud Hologram Inc. Develops Neural Network-Based Quantum-Assisted Unsupervised Data Clustering Technology

SHENZHEN, China, May 16, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (HOLO), (“HOLO” or the "Company"), a technology service provider, announced the development of a neural network-based quantum ...
The Next Web

Machine learning: What’s the difference between supervised and unsupervised?

Machine learning, the subset of artificial intelligence that teaches computers to perform tasks through examples and experience, is a hot area of research and development. Many of the applications we ...
ascopubs.org

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia

PROSPeCT: A Predictive Research Online System for Prostate Cancer Tasks Time to event is an important aspect of clinical decision making. This is particularly true when diseases have highly ...