GEN - Genetic Engineering and Biotechnology News

AI Tools for Cancer Pathology May Rely on Hidden Shortcuts That Impact on Predictive Power

When the performance of AI models was assessed within stratified patient subgroups, such as only high-grade breast cancers or ...

AI cancer tools may rely on 'shortcut learning' rather than genuine biological signals

Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...
ministryoftesting.com

Machine Learning (ML)

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financefeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
PNAS

Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning

Dinosaur footprints are iconic fossils, but it is challenging to identify their makers. This is illustrated by a long-standing debate about whether some footprints from the Late Triassic-Early ...
blockchain

Tesla FSD V14 Demonstrates Robust Camera-Only AI Autonomy in Severe Fog: Real-World Cybertruck Test

According to Sawyer Merritt, Tesla's Full Self-Driving (FSD) V14 system, which relies solely on camera-based AI perception, demonstrated strong performance in severe fog conditions. In a recent ...
Semiconductor Engineering

AI In Test Analytics: Promise Vs. Reality

The semiconductor industry is increasingly turning to artificial intelligence as the solution for increasing complexity in test analytics, hoping algorithms can tame the growing flood of production ...
Scientific Research Publishing

Explainable Machine Learning in Risk Management: Balancing Accuracy and Interpretability ()

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...
ascopubs.org

Development of a Machine Learning Model for Aspyre Lung Blood: A New Assay for Rapid Detection of Actionable Variants From Plasma in Patients With Non–Small Cell Lung Cancer

Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study Data ...
Frontiers

Postpartum depression risk prediction using explainable machine learning algorithms

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...