Simulation of tissue heating by magnetic fluid hyperthermia
Bibliographic record
Abstract
<strong>Objective:</strong> Magnetic fluid hyperthermia is a technique in which thermal energy is generated by magnetic nanoparticles (MNPs) that are excited by an alternating magnetic field (AC field). During hyperthermia, in-vivo monitoring of elevation of temperature relies on invasive insertion of conventional thermometers, or employment of thermo-sensitive cameras that lack high precision. The objective of this manuscript is to provide a mathematical approach to better estimate elevation of temperature and its profile after hyperthermia of MNPs inside an AC field.<br /> <strong>Methods:</strong> To this end, we first show that temperature profile due to hyperthermia of iron oxide MNPs at 10, 25, and 50 mg/ml are concentration dependent. Then by using best-fit polynomial equations, we show that the temperature profile for any given concentration of the same iron oxide MNPs can be traced to close approximation. Thermodynamic heat transfer equations were then used to graph the distribution of temperature in a tissue with a known heat capacity and conductivity parameters.<br /> <strong>Results:</strong> The resulting MatLab software simulation provides the thermal profile of a hypothetical tumor placed adjacent to a muscle tissue.<br /> <strong>Conclusions:</strong> In conclusion, the proposed mathematical approach can closely estimate the temperature profile of magnetic fluid hyperthermia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".