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Protons and neutrons, collectively called nucleons, are packed together tightly in a nucleus. With a radius of about 10−15 meters, a nucleus is quite small compared to the radius of the entire atom, which is about 10−10 meters. Nuclei are extremely dense compared to bulk matter, averaging 1.8 × 1014 grams per cubic centimeter. If the earth’s density were equal to the average nuclear density, the earth’s radius would be only about 200 meters.
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The process of converting very light nuclei into heavier nuclei is also accompanied by the conversion of mass into large amounts of energy, a process called fusion. The principal source of energy in the sun is a net fusion reaction in which four hydrogen nuclei fuse and ultimately produce one helium nucleus and two positrons.
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Nuclear transmutation is the conversion of one nuclide into another. It can occur by the radioactive decay of a nucleus, or the reaction of a nucleus with another particle. The first manmade nucleus was produced in Ernest Rutherford’s laboratory in 1919 by a transmutation reaction, the bombardment of one type of nuclei with other nuclei or with neutrons. Rutherford bombarded nitrogen-14 atoms with high-speed α particles from a natural radioactive isotope of radium and observed...
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Before mRNAs are exported to the cytoplasm, it is crucial to check each mRNA for structural and functional integrity. Eukaryotic cells use several different mechanisms, collectively known as mRNA surveillance, to look for irregularities in mRNAs. Irregular or aberrant mRNA are rapidly degraded by various enzymes. If a defective mRNA escapes the surveillance, it would be translated into a protein which would either be non-functional or not function properly. One of the primary irregularities in...
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Controlled nuclear fission reactions are used to generate electricity. Any nuclear reactor that produces power via the fission of uranium or plutonium by bombardment with neutrons has six components: nuclear fuel consisting of fissionable material, a nuclear moderator, a neutron source, control rods, reactor coolant, and a shield and containment system.
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Artificial intelligence in nuclear medicine.

Flemming Littrup Andersen1,2, Adam Espe Hansen2,3

  • 1Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet, Copenhagen 2100, Denmark.

The British Journal of Radiology
|January 21, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances nuclear medicine diagnostics and treatment. While AI integration offers revolutionary potential, transitioning these developments from research to widespread clinical use remains a significant challenge.

Keywords:
PETSPECTartificial intelligencegenerative AInuclear medicineregulations

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Area of Science:

  • Nuclear Medicine
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Artificial intelligence (AI), particularly Deep Learning (DL) and convolutional neural networks (CNN), has advanced rapidly due to hardware improvements like GPUs.
  • AI integration in medical imaging promises to revolutionize nuclear medicine through accelerated acquisition, enhanced quality, advanced generation, interpretation assistance, and treatment planning.
  • Clinical AI applications exist across specialties like oncology, neurology, and radionuclide therapy, with potential for broader patient access via standardized procedures.

Purpose of the Study:

  • To review current AI applications in nuclear medicine.
  • To discuss the challenges and opportunities in transitioning AI from development to clinical implementation.
  • To highlight the potential of AI in optimizing treatment strategies, risk assessment, and patient outcomes.

Main Methods:

  • Review of current AI applications across the nuclear medicine imaging workflow, including acquisition, reconstruction, post-processing, analysis, and decision support.
  • Discussion of the transition from AI development to clinical maturity, noting the low percentage of AI applications reaching beyond prototyping.
  • Focus on challenges and opportunities for AI implementation in nuclear medicine.

Main Results:

  • AI integration offers significant potential to improve efficiency and outcomes in nuclear medicine.
  • Few AI developments in nuclear medicine have achieved commercial maturity, with most applications still in the development or prototyping phase.
  • AI can help standardize advanced imaging, making it accessible to smaller clinics and benefiting a wider patient population.

Conclusions:

  • AI holds immense promise for nuclear medicine, but significant hurdles exist in clinical implementation.
  • Further research and development are needed to overcome challenges and fully realize AI's potential in nuclear medicine diagnostics and treatment.
  • Focusing on the transition from development to clinical practice is crucial for widespread AI adoption in the field.