AIMC Topic: Quantum Theory

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Quantum Descriptor-Based Machine-Learning Modeling of Thermal Hazard of Cyclic Sulfamidates.

Journal of chemical information and modeling
Cyclic sulfamidates are commonly used building blocks in organic synthesis. Correct classification of their thermal criticality is crucial for the safe use of these compounds in process development and scale-up. In this study, building on our earlier...

Machine Learning-Enhanced Calculation of Quantum-Classical Binding Free Energies.

Journal of chemical theory and computation
Binding free energies are key elements in understanding and predicting the strength of protein-drug interactions. While classical free energy simulations yield good results for many purely organic ligands, drugs, including transition metal atoms, oft...

Robust Quantum Reservoir Learning for Molecular Property Prediction.

Journal of chemical information and modeling
Machine learning has been increasingly utilized in the field of biomedical research to accelerate the drug discovery process. In recent years, the emergence of quantum computing has led to the extensive exploration of quantum machine learning algorit...

Quantum-Embedded Graph Neural Network Architecture for Molecular Property Prediction.

Journal of chemical information and modeling
Accurate prediction of molecular properties is crucial for accelerating the development of new drugs, and quantum machine learning (QML) holds great promise in this domain. A typical QML pipeline comprises two core stages: encoding classical data int...

Quantum Oncology: The Applications of Quantum Computing in Cancer Research.

Journal of medical systems
A global technological race is underway to develop increasingly powerful and precise quantum computers. As a transformative computing paradigm, quantum computing offers the potential for exponentially accelerating specific algorithms, thereby providi...

Hybrid classical and quantum computing for enhanced glioma tumor classification using TCGA data.

Scientific reports
Gliomas are the most prevalent malignant primary brain tumors and present diagnostic challenges due to varying survival rates and treatment responses between low-grade gliomas (LGGs) and high-grade gliomas (HGGs). Accurate classification is crucial f...

Use of hybrid quantum-classical algorithms for enhancing biomarker classification.

PloS one
Quantum machine learning (QML) combines quantum computing with machine learning, offering potential for solving intricate problems. Our research delves into QML's application in identifying gene expression biomarkers for clear cell renal cell carcino...

Unlocking clinical quantum oncology through quantum control.

European journal of cancer (Oxford, England : 1990)
Quantum technologies present a transformative frontier for oncology, promising significant advancements in diagnostics, treatment precision, and drug discovery. The clinical realization of this potential is fundamentally reliant on mastering quantum ...

Relaxation-assisted reverse annealing on nonnegative/binary matrix factorization.

PloS one
Quantum annealing has garnered significant attention as meta-heuristics inspired by quantum physics for combinatorial optimization problems. Among its many applications, nonnegative/binary matrix factorization stands out for its complexity and releva...

Towards a Possible Definition of Consciousness.

Bio Systems
There is no consensus about what cognition and its emergent form, consciousness, are. Yet this article proposes a new definition of consciousness. As many researchers, philosophers and other thinkers believe that life means cognising, this new defini...