Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Simple, sensitive and economical spectrophotometric methods have been developed for the determination of cefixime in pure form. This method is based on the reaction of cefixime as n-electron donor with chloranil to give highly colored complex in ethanol which is absorb maximally at 550 nm. Beer's law is obeyed in the concentration ranges 5-250 µg ml-1 with high apparent molar absorptivities of 1.52×103 L.mole-1. cm-1.

the physical paraneters of oxadizole derivaties as donor molecules have been measured the charge transfer and methanol as solvent have been estimated from the electonic spectra

In this research, the dynamics process of charge transfer from the sensitized  D35CPDT dye to tin(iv) oxide( ) or titanium dioxide (  ) semiconductors are carried out by using a quantum model for charge transfer. Different chemical solvents Pyridine, 2-Methoxyethanol. Ethanol, Acetonitrile, and Methanol have been used with both systems as polar media surrounded the systems. The rate for charge transfer from photo-excitation D35CPDTdye and injection into the conduction band of  or  semiconductors vary from a  to  for system and from a   to  for the system, depending on the charge transfer parameters strength coupling, free energy, potential of donor and acceptor in the system. The charge transfer rate in D35CPDT /  the system is

In this research, the dynamics process of charge transfer from the sensitized  D35CPDT dye to tin(iv) oxide( ) or titanium dioxide (  ) semiconductors are carried out by using a quantum model for charge transfer. Different chemical solvents Pyridine, 2-Methoxyethanol. Ethanol, Acetonitrile, and Methanol have been used with both systems as polar media surrounded the systems. The rate for charge transfer from photo-excitation D35CPDTdye and injection into the conduction band of  or  semiconductors vary from a  to  for system and from a   to  for the system, depending on the charge transfer parameters strength coupling, free energy, potential of donor and acceptor in the system. The charge transfer rate in D35CPDT /  the syst

Charge transfer complex formation method has been applied for the spectrophotometric determination of erythromycin ethylsuccinate, in bulk sample and dosage form. The method was accurate, simple, rapid, inexpensive and sensitive depending on the formed charge- transfer complex between cited drug and, 2,3- Dichloro-5,6-dicyano-p- benzoquinone (DDQ) as a chromogenic reagent. The formed complex shows absorbance maxima at 587 nm against reagent blank. The calibration graph is linear in the ranges of (10 - 110) μg.mL-1 with detection limit of 0.351μg.mL-1. The results show the absence of interferences from the excipients on the determination of the drug. Therefore the proposed method has been successfully applied for the determination of eryth