What is he best known for?
The fields of study he is best known for:
- Ecology
- Oceanography
- Internal medicine
His primary areas of investigation include Climate change, Oceanography, Sedimentation, Hydrology and Physical geography.
The various areas that Martin Schmid examines in his Climate change study include Biogeochemical cycle and Surface water.
Martin Schmid combines subjects such as Carbon dioxide and Magma with his study of Oceanography.
His Sedimentation research is multidisciplinary, incorporating perspectives in Environmental chemistry, Organic matter, Atmosphere and Carbon cycle.
His study in the field of Water well is also linked to topics like Isotope fractionation.
His work in the fields of Extinction risk from global warming overlaps with other areas such as Vulnerability assessment and Cloud cover.
His most cited work include:
- Rapid and highly variable warming of lake surface waters around the globe (535 citations)
- A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis (281 citations)
- Eutrophication of ancient Lake Ohrid: Global warming amplifies detrimental effects of increased nutrient inputs (130 citations)
What are the main themes of his work throughout his whole career to date?
Martin Schmid mostly deals with Hydrology, Atmospheric sciences, Stratification, Climate change and Oceanography.
Martin Schmid has included themes like Water column, Turbidity, Hypolimnion, Nutrient and Hydropower in his Hydrology study.
His study looks at the intersection of Water column and topics like Surface water with Biogeochemistry.
The various areas that Martin Schmid examines in his Hypolimnion study include Environmental chemistry and Sediment.
His work carried out in the field of Atmospheric sciences brings together such families of science as Climatology and Heat flux.
His study focuses on the intersection of Climate change and fields such as Biogeochemical cycle with connections in the field of Anaerobic oxidation of methane.
He most often published in these fields:
- Hydrology (25.52%)
- Atmospheric sciences (12.41%)
- Stratification (11.72%)
What were the highlights of his more recent work (between 2018-2021)?
- Hydrology (25.52%)
- Artificial intelligence (4.83%)
- Climate change (11.03%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Hydrology, Artificial intelligence, Climate change, Deep learning and Environmental chemistry.
His study ties his expertise on Renewable energy together with the subject of Hydrology.
In his study, Optical coherence tomography is strongly linked to Fundus, which falls under the umbrella field of Artificial intelligence.
His Climate change research includes elements of Stratification and Atmospheric sciences.
His studies in Atmospheric sciences integrate themes in fields like Limnic eruption and Inlet.
His studies deal with areas such as Precision and recall, Coding and Discriminative model as well as Deep learning.
Between 2018 and 2021, his most popular works were:
- A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis (281 citations)
- Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study (55 citations)
- State of the Climate in 2018 (35 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Internal medicine
- Oceanography
His primary scientific interests are in Climatology, Hydrology, Meta-analysis, Citation index and Medical physics.
Martin Schmid undertakes multidisciplinary investigations into Hydrology and Free cooling in his work.
The study incorporates disciplines such as Test, Contingency table and Medical imaging in addition to Meta-analysis.
His Medical imaging study which covers Deep learning that intersects with Discriminative model.
In his study, Martin Schmid carries out multidisciplinary Citation index and Sample research.
His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning and Coding.
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