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'''[[Clinical pathology]]''' (US, UK, Ireland, Commonwealth, Portugal, Brazil, Italy), '''laboratory medicine''' (Germany, Romania, Poland, Eastern Europe), '''clinical analysis''' (Spain), or '''clinical/medical biology''' (France, Belgium, Netherlands, Austria, North and West Africa) is a medical specialty concerned with the diagnosis of disease based on the [[laboratory]] analysis of bodily fluids, such as blood, urine, and tissues using the tools of chemistry, microbiology, hematology, and molecular pathology. Clinical pathologists work in close collaboration with clinical scientists (clinical biochemists, clinical microbiologists, etc.), medical technologists, [[hospital]] administrators, and referring physicians to ensure the accuracy and optimal utilization of laboratory testing. This specialty requires a medical residency and should not be confused with biomedical science, which is not necessarily related to medicine.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Clinical pathology is one of two major divisions of pathology, the other being [[anatomical pathology]]. Often, pathologists practice both anatomical and clinical pathology, a combination sometimes known as general pathology. The distinction between clinical and anatomic pathology is increasingly blurred by the introduction of technologies that require new expertise and the need to provide patients and referring physicians with integrated diagnostic reports. ('''[[Clinical pathology|Full article...]]''')<br />
[[Information]] is the cornerstone of [[research]], from experimental data/[[metadata]] and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging [[laboratory information management system]]s (LIMS) to transform this large information load into useful scientific findings. The development of [[mathematical model]]s that can predict the properties of biological systems is the holy grail of [[computational biology]]. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... ('''[[Journal:Ten simple rules for managing laboratory information|Full article...]]''')<br />
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''Recently featured'': [[Anatomical pathology]], [[Information]], [[Clinical laboratory]]
''Recently featured'':
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{{flowlist |
* [[Journal:Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology|Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology]]
* [[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]
* [[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]
}}

Latest revision as of 18:03, 10 June 2024

Fig2 Berezin PLoSCompBio23 19-12.png

"Ten simple rules for managing laboratory information"

Information is the cornerstone of research, from experimental data/metadata and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems (LIMS) to transform this large information load into useful scientific findings. The development of mathematical models that can predict the properties of biological systems is the holy grail of computational biology. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... (Full article...)

Recently featured:

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