David Kovacs

Feb 3, 2025 | jnm.snmjournals.org | David Kovacs |Claes Nøhr Ladefoged |Jacob Bak Rosenkjær |Fatima Mawassi

The advent of artificial intelligence (AI) in medical imaging and nuclear medicine could revolutionize our approach to diagnosing and treating complex conditions. Our recent paper, “Clinical Evaluation of Deep Learning for Tumor Delineation on 18F-FDG PET/CT of Head and Neck Cancer,” (1) showcases the potential of in-house AI in clinical practice. Clinically, we often find ourselves in need of a legitimate path to apply in-house developments.

Sep 25, 2024 | concertmonkey.be | David Kovacs

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Jun 28, 2024 | pubs.aip.org | Aerospace Engineering |Jinzhe Zeng |Philipp Pracht |David Kovacs

Multicomponent macromolecular mixtures often form higher-order structures, which may display non-ideal mixing and aging behaviors. In this work, we first propose a minimal model of a quaternary system that takes into account the formation of a complex via a chemical reaction involving two macromolecular species; the complex may then phase separate from the buffer and undergo a further transition into a gel-like state.

Jun 24, 2024 | pubs.aip.org | Philipp Pracht |Jinzhe Zeng |David Kovacs

The authors previously developed a divide-and-conquer (DC)-based non-local excited-state calculation method for large systems using dynamical polarizability [Nakai and Yoshikawa, J. Chem. Phys. 146, 124123 (2017)]. This method evaluates the excitation energies and oscillator strengths using information on the dynamical polarizability poles.

Jun 21, 2024 | pubs.aip.org | Jinzhe Zeng |Philipp Pracht |David Kovacs

We formulate a thermodynamic theory applicable to both classical and quantum systems. These systems are depicted as thermodynamic system–bath models capable of handling isothermal, isentropic, thermostatic, and entropic processes. Our approach is based on the use of a dimensionless thermodynamic potential expressed as a function of the intensive and extensive thermodynamic variables.