AI Medical Compendium Journal:
Science (New York, N.Y.)

Showing 41 to 50 of 169 articles

Using machine learning to decode animal communication.

Science (New York, N.Y.)
New methods promise transformative insights and conservation benefits.

Mitigating bias in AI at the point of care.

Science (New York, N.Y.)
Promoting equity in AI in health care requires addressing biases at cli nical implementation.

Implications of predicting race variables from medical images.

Science (New York, N.Y.)
AI-predicted race variables pose risks and opportunities for studying health disparities.

Leveraging artificial intelligence in the fight against infectious diseases.

Science (New York, N.Y.)
Despite advances in molecular biology, genetics, computation, and medicinal chemistry, infectious disease remains an ominous threat to public health. Addressing the challenges posed by pathogen outbreaks, pandemics, and antimicrobial resistance will ...

How AI can distort human beliefs.

Science (New York, N.Y.)
Models can convey biases and false information to users.

Could chatbots help devise the next pandemic virus?

Science (New York, N.Y.)
An MIT class exercise suggests AI tools can be used to order a bioweapon, but some are skeptical.

AI and the transformation of social science research.

Science (New York, N.Y.)
Careful bias management and data fidelity are key.

Neuromorphic sensorimotor loop embodied by monolithically integrated, low-voltage, soft e-skin.

Science (New York, N.Y.)
Artificial skin that simultaneously mimics sensory feedback and mechanical properties of natural skin holds substantial promise for next-generation robotic and medical devices. However, achieving such a biomimetic system that can seamlessly integrate...

Relating enhancer genetic variation across mammals to complex phenotypes using machine learning.

Science (New York, N.Y.)
Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challe...

Top-down design of protein architectures with reinforcement learning.

Science (New York, N.Y.)
As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approa...