Improvising the performance of machine learning for applications in the field of computer science leads to create new algorithms. As these are being optimized, using the algorithms of the classical ...

The bookshelf problem (which computer scientists call the “list labeling” problem) is one of the most basic topics in the field of data structures. “It’s the kind of problem you’d teach to freshman or ...

This research investigates the efficacy of various machine learning algorithms in detecting malware. Utilizing a dataset of 20,000 observations with 33 features,28 classification algorithms are ...

We present a high-throughput, end-to-end pipeline for organic crystal structure prediction (CSP)─the problem of identifying the stable crystal structures that will form from a given molecule based ...

In Optica Quantum, Okinawa Institute of Science and Technology (OIST) researchers propose the first practical application of ...

Medulloblastoma the most common malignant pediatric brain tumor with a high risk of metastasis and poor survival outcomes.

Researchers developed a two-stage ML model to predict coating degradation by linking environmental factors to physical changes and corrosion. The framework enables more accurate, data-driven ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

xii, 376 pages : 24 cm Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research ...

Graphical AbstractFour hundred participants (95 healthy, 94 hypertrophic cardiomyopathy, 95 AL, and 116 ATTR) from 56 institutions were included (269 men aged 58.5 [48.4–69.4] years). A 3-stage ML ...