RETRACTED ARTICLE: Artificial intelligence and machine learning in precision and genomic medicine
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Post-publication record
- Nature
- Retraction
- Reason
- Computer-Aided Content or Computer-Generated Content;Concerns/Issues about Authorship/Affiliation;Concerns/Issues about Article;Investigation by Company/Institution;Investigation by Journal/Publisher;Unreliable Results and/or Conclusions;
- Date
- 4/26/2025 0:00
- Flagged by OpenAlex?
- Yes
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement — it reports them as false, which reads as “fine”.
Abstract
The advancement of precision medicine in medical care has led behind the conventional symptom-driven treatment process by allowing early risk prediction of disease through improved diagnostics and customization of more effective treatments. It is necessary to scrutinize overall patient data alongside broad factors to observe and differentiate between ill and relatively healthy people to take the most appropriate path toward precision medicine, resulting in an improved vision of biological indicators that can signal health changes. Precision and genomic medicine combined with artificial intelligence have the potential to improve patient healthcare. Patients with less common therapeutic responses or unique healthcare demands are using genomic medicine technologies. AI provides insights through advanced computation and inference, enabling the system to reason and learn while enhancing physician decision making. Many cell characteristics, including gene up-regulation, proteins binding to nucleic acids, and splicing, can be measured at high throughput and used as training objectives for predictive models. Researchers can create a new era of effective genomic medicine with the improved availability of a broad range of datasets and modern computer techniques such as machine learning. This review article has elucidated the contributions of ML algorithms in precision and genome medicine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Medical Oncology
- Topic
- Genetics, Bioinformatics, and Biomedical Research
- Field
- Biochemistry, Genetics and Molecular Biology
- Canadian institutions
- Emergent BioSolutions (Canada)
- Funders
- —
- Keywords
- Precision medicineArtificial intelligencePersonalized medicineMachine learningHealth careComputer scienceInferenceBiobankProcess (computing)Data scienceDeep learningPersonalizationBioinformaticsMedicineBiology
- Has abstract in OpenAlex
- yes